1. Executive Summary

The United States Department of Defense (DoD) is in the midst of a foundational paradigm shift regarding the procurement, deployment, and operational integration of unmanned aerial systems (UAS). Driven by strategic initiatives such as Replicator, the DoD aims to field all-domain attritable autonomous systems at an unprecedented scale to offset the quantitative and anti-access/area-denial (A2/AD) advantages of near-peer competitors.¹ This initiative represents a recognition that the character of warfare has fundamentally changed; massed, low-cost precision strike capabilities are replacing solitary, exquisite platforms as the primary arbiters of tactical success.³ However, while institutional focus and capital investment are overwhelmingly directed toward the kinematic capabilities and production scale of these airframes, a critical operational vulnerability remains largely unaddressed: the systemic enterprise architecture required to conduct accurate, near-real-time post-strike Battle Damage Assessment (BDA).

When hundreds of autonomous assets engage a target matrix simultaneously, the resulting battlespace becomes highly opaque. The traditional methodology for evaluating strike effectiveness relies heavily on centralized Intelligence, Surveillance, and Reconnaissance (ISR) assets, supported by human-in-the-loop Processing, Exploitation, and Dissemination (PED) workflows.⁴ These legacy systems, developed for deliberate operations, are entirely unsuited for the speed, volume, and complexity of autonomous swarm engagements. The inability to rapidly verify target destruction, attribute specific kinetic effects to individual platforms amidst heavy electronic warfare, and dynamically update the Common Operating Picture (COP) creates severe situational awareness deficits for commanders operating at echelon.⁵

This strategic report identifies the doctrinal, technological, and enterprise-level methodology gaps that DoD leadership must address to ensure swarm technologies yield decisive operational advantages. The analysis evaluates the physical challenges of massed detonations, the necessity of multi-modal sensor fusion in degraded environments, the imperative for edge-based neuromorphic processing, and the legal and ethical requirements for establishing accountability in AI-driven targeting.⁸ Failure to modernize the BDA enterprise concurrently with UAS procurement risks fielding a force capable of mass destruction but incapable of operational assessment, leading to inefficient resource allocation, disrupted mission command, and significant strategic liability. Addressing these methodology gaps is not a secondary sustainment concern; it is a primary warfighting requisite for the future joint force.

2. Strategic Context: The Proliferation of Autonomous Mass

The character of contemporary warfare is undergoing a rapid evolution characterized by the democratization of precision fires. For decades, the United States maintained a near-monopoly on precision strike capabilities, relying on deep magazines of advanced munitions delivered by highly survivable, yet incredibly expensive, platforms.³ The proliferation of cheap drone technology has fundamentally altered this landscape, rendering traditional models of air dominance and force protection increasingly vulnerable.³

2.1 The Replicator Initiative and the Offset Strategy

The DoD’s introduction of the Replicator initiative signifies a concerted effort to allocate resources toward the fielding and deployment of all-domain expendable autonomous capabilities at a scale capable of yielding significant operational impact.¹¹ The core objective of this initiative is to thwart the asymmetric advantages of adversaries—particularly the People’s Liberation Army (PLA) of China—through the application of many, small, “attritable” weapons and combat platforms.² The PLA is rapidly advancing its drone capabilities by developing more autonomous systems and acquiring them at scale.³ Without deep magazines of autonomous capabilities and the supporting architectures to manage them, the United States risks having its distributed warfighting strategies overwhelmed by massed drone attacks.³

Replicator poses an opportunity for the U.S. Army and the broader Joint Force to continuously transform concepts, capabilities, and capacities.² However, as the DoD integrates lessons learned from executing the first iterations of the Replicator initiative, leadership must recognize that scale alone is an insufficient countermeasure.¹¹ A pronounced production advantage must be paired with a concerted innovation effort focused on optimizing tactical efficacy.¹¹ Efficacy is directly tied to the ability to assess, adapt, and redirect force—all of which rely entirely on the BDA enterprise.

2.2 Operational Lessons from Contemporary Conflicts

Observations from the Russo-Ukrainian war and conflicts in the Middle East provide a stark preview of the future battlefield. The front lines have expanded into wide “kill zones” where drones detect and strike targets across vast areas with unprecedented precision.¹³ Ukrainian commanders have leveraged the relatively low cost and high accuracy of these systems to develop new tactical concepts, employing first-person-view (FPV) drones for real-time reconnaissance and loitering munitions for precision strikes against enemy armor, artillery, and command posts.¹⁵

The integration of UAS with artillery has been particularly transformative, enabling real-time adjustments of fire and immediate battle damage assessment, thereby changing the entire calculus of fire support.¹⁵ However, this operational success is currently predicated on heavy human-in-the-loop involvement. Warfighters manually pilot FPVs, manually assess the video feeds, and manually call for adjustments. As conflicts scale and electronic warfare environments become more hostile, this manual methodology becomes unsustainable. The Ukrainian military’s stated objective is to eventually remove warfighters from direct combat and replace them with autonomous unmanned systems, recognizing that human capacity to process and fuse large amounts of data is a critical vulnerability.¹⁶

Furthermore, operations in Syria demonstrate the evolving use of massed systems. During Operation Spring Shield in 2020, Turkish forces grouped armed UAVs together in significant numbers—described as “swarms”—with the specific aim of overwhelming opponent air defenses.¹⁷ This approach negated the need to ensure that ground-based air defenses were fully neutralized prior to engagement, as the drones themselves acted as both the sensor and the kinetic effector.¹⁷ As these tactics evolve from remote-controlled operations to fully autonomous algorithmic swarms, the necessity for an automated, enterprise-level BDA capability becomes paramount.

3. The Doctrinal Chasm: Legacy BDA Frameworks Versus Swarm Velocity

Current DoD joint targeting doctrine is primarily codified within publications such as Joint Publication 3-60 (JP 3-60). This doctrinal framework was meticulously developed for an era of deliberate, single-platform precision strikes and relies upon methodologies that represent a fundamental mismatch with the operational realities of autonomous drone swarms.¹⁸

3.1 The Structural Limitations of Joint Publication 3-60

Targeting encompasses many processes, all linked and logically guided by the joint targeting cycle, which continuously seeks to analyze, identify, develop, validate, assess, and prioritize targets for engagement.¹⁹ Combat assessment measures whether desired effects are created, if objectives are achieved, and what next steps are required.⁴ According to established doctrine, the BDA process is divided into distinct, chronological phases.

Phase I BDA focuses on initial functional damage assessment. This initial reporting is generally expected within a 24-hour window after the information becomes available.⁴ Phase II assesses specific target element damage. Phase III, known as Target System Assessment, evaluates the broader impact on an adversary’s overall capabilities. Doctrine explicitly describes Phase III as a “data-intensive process” that “typically requires weeks to months to accumulate the data to assess the impact on the target system”.⁴

In the context of a massed drone strike, where hundreds of loitering munitions or small FPV drones may engage an enemy defensive line within a span of minutes, a 24-hour feedback loop is tactically obsolete. Autonomous swarm logic relies on instantaneous, continuous feedback to effectively reallocate surviving airborne assets to undestroyed targets.²⁰ If a swarm must hold position or return to base to wait for external ISR platforms to conduct a Phase I assessment, the principles of mass, momentum, and operational tempo are entirely forfeited.

Furthermore, JP 3-60 explicitly acknowledges a critical methodology gap: the limited availability of collection assets. The doctrine states that Intelligence, Surveillance, and Reconnaissance (ISR) and Processing, Exploitation, and Dissemination (PED) assets are “usually limited in number”.⁴ In operational reality, collection requirements for target development, Joint Intelligence Preparation of the Operational Environment (JIPOE), and indications and warnings frequently take precedence over combat assessment.⁴ Relying on these scarce, highly centralized assets to monitor and evaluate hundreds of simultaneous drone strikes is mathematically and operationally untenable.

3.2 The Operational Risk of Estimated Damage Assessment (EDA)

In scenarios where physical confirmation of damage is unavailable—a highly probable situation in heavily contested, A2/AD airspace where dedicated BDA ISR assets cannot survive—doctrine permits the use of Estimated Damage Assessment (EDA).⁴ The EDA methodology anticipates damage by utilizing probabilistic models based on the known effectiveness of specific weapons against specific target types. This allows a commander to accept operational risk in the absence of definitive visual data.⁴

Relying on EDA methodologies for massed drone strikes introduces profound strategic and tactical risk. Unmanned systems, particularly the lower-cost “attritable” models envisioned by the Replicator initiative, possess highly variable failure rates, payload yields, and navigation vulnerabilities compared to traditional munitions.²¹ If a swarm of 500 autonomous drones is launched against a mechanized brigade, and the EDA methodology assumes an 85% success rate based on pre-flight probabilities, operational commanders may erroneously advance friendly maneuver forces into fully intact enemy defensive networks. Alternatively, if commanders lack confidence in the EDA due to known high attrition rates of small UAS, they may authorize continuous re-attacks on already destroyed targets, rapidly depleting the finite magazine depth of the swarm and stressing logistical supply chains.²⁰

3.3 Munitions Effectiveness Assessment (MEA) Latency

Another significant doctrinal gap exists within the Munitions Effectiveness Assessment (MEA) framework. MEA evaluates whether a weapon functioned as engineered and intended.⁴ Currently, MEA data generation relies on a long-term feedback loop. The intelligence gathered is typically funneled into the Joint Munitions Effectiveness Manual (JMEM) revision process to inform future capability analysis, rather than providing an immediate tactical adjustment for ongoing engagements.⁴

For drone swarms to function as intelligent, adaptive combat systems, MEA must transition from a retrospective analytical tool to a near-real-time tactical capability. If an adversary introduces a novel electronic warfare (EW) jamming technique, a new directed energy weapon, or a physical countermeasure that causes a specific munition to fail in the terminal phase, the swarm must immediately recognize this failure.²³ It must then rapidly shift tactics, alter approach trajectories, or switch sensor modalities. A delayed MEA feedback loop renders the entire massed swarm highly susceptible to a single, rapidly deployed countermeasure, potentially neutralizing the entire force package before human analysts even register the failure.²²

4. The Physical and Environmental Realities of Massed Strikes

The visual and electromagnetic environment resulting from a massed drone strike creates immense physical barriers to accurate post-strike assessment. The sheer density of kinetic events generates systemic interference that routinely blinds traditional optical sensor arrays, necessitating a complete overhaul of how autonomous systems perceive the post-strike battlespace.

4.1 Visual Occlusion, Thermal Blooming, and Electromagnetic Chaos

When kinetic energy weapons, such as the shaped charges or fragmentation payloads carried by loitering munitions, impact their targets, they deposit massive amounts of kinetic and thermal energy, generating highly localized destruction.²⁴ In a coordinated mass strike involving dozens or hundreds of detonations within a tightly confined geographical area, the resulting physical phenomena actively obscure the battlefield from observation.

The primary impediment is particulate obscuration. Pulverized concrete, displaced earth, fragmented armor, and combustion smoke create a dense, persistent aerosol layer over the target area. Traditional visual (RGB) cameras, which are heavily relied upon for FPV targeting and basic intelligence gathering, cannot penetrate this layer.¹⁰

Simultaneously, the heat generated by consecutive explosions saturates infrared (IR) sensors, a phenomenon known as thermal blooming. An incoming follow-on drone attempting to assess the damage of a preceding strike wave will find its thermal optics blinded by the residual heat signature of the destroyed target, the burning terrain, and the atmospheric distortion.¹⁰ This makes it nearly impossible for basic algorithms to differentiate between a burning, destroyed vehicle and the still-intact armor positioned adjacent to it.

Furthermore, these massed detonations, coupled with active adversary electronic warfare and the necessary friendly jamming meant to protect the swarm from counter-UAS systems, create a highly contested and chaotic electromagnetic spectrum (EMS).²¹ The denial of the EMS affects friendly units just as severely as adversaries.²¹ If a swarm is programmed to strike in rapid succession, the drones arriving at the target area moments after the initial wave are flying into an environment that is visually, thermally, and electromagnetically opaque. Without specialized, multi-modal methodologies to see through this post-strike fog, follow-on drones cannot conduct BDA, nor can they accurately acquire secondary targets.

4.2 The Imperative of Multi-Modal Sensor Fusion

To overcome these severe physical limitations, the enterprise BDA methodology must definitively shift from single-sensor reliance to automated, multi-modal sensor fusion driven by advanced neural networks.¹⁰

Recent research in remote sensing and disaster monitoring demonstrates that relying solely on Electro-Optical (EO) or IR sensors is entirely insufficient for highly obscured environments.¹⁰ Advanced methodologies necessitate the integration of Synthetic Aperture Radar (SAR) with high-resolution UAV-based optical and thermal imagery.¹⁰ SAR possesses the unique physical capability to penetrate dense smoke, heavy cloud cover, and airborne obscurants, providing high-fidelity topological mapping and structural analysis of the target area regardless of visual conditions.¹⁰

Implementing this level of multi-modal fusion across a swarm requires highly sophisticated neural network architectures capable of operating on constrained hardware. For example, hybrid learning frameworks utilizing Vision Transformers (such as FPANet) can capture both local textures and global spatial dependencies to achieve robust segmentation from SAR data under cloudy or smoky conditions.¹⁰ Simultaneously, models designed specifically for the synergistic fusion of thermal and RGB imagery (such as DualSegFormer) ensure high-fidelity target delineation even when visibility is partially compromised.¹⁰ Other optimization algorithms, such as customized versions of YOLOv8 utilizing High Intersection over Union (HIoU) loss functions, dynamically adjust the weight of various visual components to achieve precise target localization despite background noise.²⁷

The core enterprise challenge for the DoD is not merely acquiring these diverse sensors, but engineering the algorithms that allow attritable, low-cost drones to fuse this disparate data organically and autonomously.

5. Enterprise Architecture and Telemetry Bottlenecks

The defining characteristic of a functional drone swarm is its interconnectedness—the ability of multiple independent agents to share data and act cooperatively.²⁰ However, this critical connectivity creates a massive structural vulnerability when applied to traditional BDA methodologies, which rely on moving large packets of raw data back to human analysts.

5.1 The Bandwidth Paradox and Electromagnetic Contestation

A swarm comprising hundreds of drones, each equipped with visual, thermal, SAR, and telemetry sensors, generates an astronomical volume of data continuously.⁹ In a peacetime, uncontested environment—such as a disaster response scenario or a domestic training exercise—streaming high-definition multi-modal data from multiple platforms to a centralized Ground Control Station (GCS) is feasible via 5G networks and unhindered line-of-sight communications.²⁹ In a large-scale combat operation (LSCO) against a near-peer adversary, this data architecture will immediately collapse.

Adversaries will employ aggressive electronic warfare (EW), attempting to jam the radio-frequency links required for both command and control (C2) and data transmission.²³ Furthermore, wide-area and wide-spectrum jamming operations inherently affect both friendly and enemy units. To operate effectively, friendly forces must meticulously map, interpret, and deconflict their own EMS usage to avoid electronic fratricide.²¹ Consequently, the available bandwidth for a swarm operating over a contested target area will be severely constrained, highly intermittent, or entirely denied for extended periods.

5.2 Edge Computing and Semantic Compression Methodologies

To successfully execute BDA under these highly contested conditions, the fundamental methodology of data processing must be inverted. Instead of transmitting raw, high-bandwidth data (such as live video feeds or raw radar returns) back to human analysts for processing, the data must be analyzed autonomously on the drone itself, and only the resulting assessment transmitted. This architectural shift relies on edge computing and semantic compression.³¹

Onboard edge processing capabilities drastically reduce latency by analyzing data locally rather than transmitting it to remote servers.³¹ From a practical standpoint, instead of attempting to transmit a gigabyte of video showing a burning enemy surface-to-air missile system, the drone’s onboard AI processes the video, confirms the destruction of the target against its pre-loaded threat library, and transmits a kilobyte-sized text telemetry packet: “.

This methodological shift is critical for the viability of massed autonomous operations. It transforms the swarm from a collection of “dumb” aerial cameras requiring massive, vulnerable data pipelines into a decentralized network of distributed intelligence nodes requiring minimal bandwidth to rapidly update the COP.

5.3 Neuromorphic Computing for Advanced RF Analysis

Achieving this level of sophisticated edge computing on small, attritable platforms presents a significant hardware challenge. Traditional processors consume substantial power and generate heat, which directly reduces the flight time, range, and payload capacity of small UAS.⁶ To bridge this gap, the DoD is currently funding research into advanced methodologies, particularly the application of artificial intelligence based on neuromorphic networks.⁹

Neuromorphic computing seeks to replicate human brain functionality at the nanoscale using man-made artificial neurons and synapses.⁹ This architecture allows for highly parallelized computing, with vast amounts of memory located in immediate proximity to the computing elements. The result is substantially increased processing speed coupled with drastically reduced power consumption.⁹ For military applications, a critical advantage of neuromorphic networks is their ability to operate in GHz and even THz frequency ranges.⁹ This high-frequency property allows the neural network to process microwave and RF signals directly at the carrier frequency without the power-intensive need for prior digitization or super-heterodyning.⁹

A swarm equipped with low-power neuromorphic processors could instantly analyze the complex RF signatures of a contested environment, detect the emissions of an enemy radar system, assess the functional damage of that electronic target post-strike by noting the cessation or alteration of its signal, and share that assessment across the swarm instantly, all while operating under stringent power and bandwidth limitations.

6. Methodological Paradigms for Attributing Kinetic Effects

In a legacy dispersed targeting scenario utilizing single platforms, attributing a kinetic effect is highly straightforward: one weapon is deployed against one target, and the resultant outcome is assessed directly.²¹ However, in a mass precision strike, where salvos of hundreds of effectors are launched to overwhelm point defenses at key sites, attributing kinetic effects becomes a mathematically and tactically complex “many-to-many” problem.²¹

6.1 The Challenge of Distinguishing Intercepts from Impacts

When an autonomous swarm of 200 drones assaults a heavily defended position, the adversary’s air defense artillery (ADA), electronic warfare elements, directed energy weapons, and kinetic counter-UAS systems will engage the swarm simultaneously.³ If 60 drones detonate mid-air due to kinetic intercepts, 40 crash indiscriminately due to intense EW jamming, and 100 successfully strike their designated targets, the resulting battlespace telemetry is highly ambiguous.

A critical BDA methodology gap is the enterprise’s ability to distinguish a mid-air intercept from a successful target impact based solely on the loss of platform telemetry. Currently, if an attritable drone loses connection or its telemetry suddenly ceases, the overarching system cannot definitively determine if the asset reached its objective, was neutralized en route by kinetic fire, or succumbed to electronic interference.³⁴ This lack of granular data leads to profound inaccuracies in determining enemy attrition rates and forces commanders to make decisions based on highly flawed data sets.

6.2 The “Observer-Striker” Topology and Trailing Observers

To resolve these severe attribution gaps without relying on vulnerable centralized ISR assets, the swarm itself must adopt specialized, internal structural topologies. Rather than engineering every drone in the swarm to act solely as a kinetic effector, the swarm must autonomously designate specific platforms as trailing observers or organic BDA nodes.³⁵

This methodology involves explicitly pairing loitering munitions with dedicated surveillance drones within the swarm’s algorithmic structure.³⁶ By trailing an observer drone slightly behind a kinetic wave, the observer can continuously record the terminal trajectory of the munitions. Telemetry sensors on a striking munition can transmit its GPS coordinates and flight data up to the exact millisecond before detonation.³⁵ The trailing observer then analyzes the characteristics of the medium the munition passed through—for example, assessing whether a weapon successfully penetrated a reinforced bunker roof before detonating, or if it detonated harmlessly on the exterior.³⁵

This “observer-striker” methodology allows the swarm to establish a continuous, localized, and autonomous feedback loop. The observer assesses the initial kinetic wave, utilizes its multi-modal sensors to confirm exactly which targets were successfully destroyed, and instantly assigns remaining, un-engaged targets to the second wave of strikers. This creates a highly efficient one-to-one engagement ratio that conserves the swarm’s overall ammunition depth and minimizes unintended collateral damage, operating almost entirely independently of human oversight.²⁰

7. Updating Intelligence, Mission Command, and Situational Awareness

The ultimate operational purpose of Battle Damage Assessment is not merely to compile a post-action inventory of destroyed enemy equipment. The primary objective is to continuously update the commander’s understanding of the operational environment, enabling rapid, informed decision-making and facilitating the deployment of exploitation forces.⁷

7.1 The Disconnect in the Common Operating Picture (COP)

Mission Command is a foundational doctrine based on a hybrid of centralized control and decentralized execution.³² However, there is a recognized trade-off between the proximity of forces to tactical engagements and their access to different kinds of operational information.³² As distance from the forward edge of the battlefield increases, situational awareness regarding specific tactical engagements inherently decreases.³² Put simply, the farther a commander is from the front lines, the less granular their understanding of the immediate ground truth.

Commanders located in centralized Joint Operations Centers rely entirely on the COP to understand the disposition of forces. However, if a drone swarm acts autonomously and alters its targeting priorities based on its own edge-processed BDA, the COP immediately becomes desynchronized from reality. For instance, if a swarm of 300 drones is deployed against a confirmed enemy artillery battery, and the swarm’s organic intelligence nodes determine upon arrival that the battery is actually an elaborate decoy setup, the swarm may autonomously re-route to a pre-planned secondary target.³⁷ If this decision logic and the subsequent BDA findings are not efficiently and automatically communicated back to the enterprise level, the Joint Force Commander will continue to operate under the dangerously false assumption that the primary target was engaged and neutralized.

7.2 Vision-Language Models (VLM) for Automated Reporting

To bridge this critical intelligence gap without overwhelming the constrained bandwidth of the contested EMS, the DoD must invest heavily in integrating Vision-Language Models (VLM) into the drone enterprise architecture.¹⁰ VLMs possess the advanced algorithmic capability to ingest complex, multi-modal sensor data—such as fused SAR, thermal, and RGB imagery—and translate those visual inputs into actionable, human-readable intelligence insights.¹⁰

Instead of a human intelligence analyst reviewing hours of degraded drone footage to manually compile a Phase I BDA report, a VLM operating either at the tactical edge or at a localized forward relay node can instantly generate a formatted text report for transmission. Experimental results demonstrate that VLM components show strong semantic alignment, producing highly accurate translations of complex sensor data.¹⁰ A system could autonomously transmit a concise packet: “Assault on Grid Alpha complete. 12 of 15 air defense assets neutralized. 3 assets remain active. Swarm expended 80% of kinetic payload. Recommend follow-on artillery strike.”

This methodology ensures that high-level commanders maintain acute operational awareness and can effectively exercise Mission Command without the need to micromanage the swarm’s individual tactical engagements.³²

7.3 Data Formats, API Integration, and MLOps

Processing massed drone strike data requires a robust, scalable enterprise architecture that extends far beyond the physical airframe. The current methodology of retrieving data manually from returning platforms or relying on “swivel-chair” integration by analysts manually inputting data into the COP is unworkable at scale.³⁰

The enterprise architecture must incorporate:

• Modular Data Platforms: Systems capable of receiving diverse telemetry and sensor data from various drone manufacturers, formatting it, filtering it for relevance, and converting it for immediate ingestion into joint intelligence systems.³⁰
• API Integration: The GCS must seamlessly interface with broader military intelligence databases via Application Programming Interfaces (APIs), pushing BDA updates automatically so that all adjacent units and echelons are instantly aware of target status changes.³⁸
• Machine Learning Operations (MLOps): Edge AI models will inevitably encounter novel adversary countermeasures, new camouflage techniques, or unexpected environmental variables. The enterprise requires a continuous, automated MLOps pipeline to ingest post-mission data, retrain the computer vision and BDA models, and push updated algorithmic weights back to the swarm fleet before the next operational deployment.³³

8. Legal, Ethical, and Accountability Frameworks for Autonomous BDA

As BDA methodologies inevitably shift from human-in-the-loop PED architectures to edge-AI autonomous assessments, the DoD faces significant legal, ethical, and oversight challenges. Existing international law, particularly concerning the conduct of war, is heavily predicated on human accountability and conscious decision-making.⁸

8.1 Proportionality and the Assessment of Collateral Damage

Under the established Law of Armed Conflict (LOAC), military operations must strictly adhere to the rule of proportionality. This principle dictates that the incidental loss of civilian life, injury to civilians, or damage to civilian objects must not be excessive in relation to the anticipated concrete and direct military advantage of an attack.⁴⁰ Assessing proportionality requires a deeply contextual understanding of the operational environment—a nuanced cognitive capability that current AI systems struggle to reliably frame.⁴⁰

In a massed drone strike, if an autonomous system initiates an attack, it must inherently possess the capability to assess collateral damage post-strike to determine if further engagement violates LOAC. The deployment of autonomous explosive devices, such as the Shahed-136 loitering munitions used extensively against energy infrastructure in the Russo-Ukrainian war, highlights these dangers.⁸ These systems, classified as Lethal Autonomous Weapon Systems (LAWS), engage pre-selected target groups independently.⁸

If a U.S. swarm strikes a legitimate military target but causes unintended, cascading failures in adjacent civilian infrastructure, who is accountable? The inability of an autonomous system to “frame” and contextualize the broader environment may result in the system deciding to launch follow-on attacks based not merely on incomplete, but fundamentally flawed understandings of the circumstances.⁴⁰ If the swarm lacks robust, multi-modal BDA capabilities to realize it has caused excessive collateral damage, it lacks the necessary failsafes to halt its own operations.

8.2 The “Black Box” Problem and Systemic Traceability

The deployment of LAWS raises profound questions regarding how individuals or state actors answer for crimes or errors committed on a mass scale by autonomous entities.⁸ If a swarm executes a coordinated strike utilizing its own edge-assessed BDA to determine target validity and authorize kinetic deployment, the human operator is effectively removed from the kill chain.⁴¹

Without meticulous enterprise requirements to log the decision-making process of every single drone—often referred to as the “black box” problem for autonomous systems—attributing a kinetic effect to a specific algorithm or decision node becomes impossible. Process evidence must be derived from how data is prepared, managed, analyzed, and delivered throughout the flight lifecycle.³³

If an unlawful strike occurs, or a friendly fire incident takes place, investigators must be able to pull the BDA telemetry, the sensor logs, and the specific AI decision tree to determine the root cause. Was the error due to hardware sensor failure, algorithmic bias in the targeting model, or sophisticated adversary spoofing and deception? The current institutional rush to field vast quantities of attritable drones often overlooks the massive data storage, logging architectures, and forensic methodologies required to maintain this legal compliance and operational accountability.³³

9. Strategic Recommendations and Institutional Reform

The Department of Defense’s pursuit of drone dominance, catalyzed by the rapid innovations and harsh lessons observed in theaters like Ukraine and the Middle East ¹⁴, is a strategically necessary evolution. However, deploying mass without the institutional capacity to assess its impact is strategically hollow and operationally reckless. To ensure commanders possess accurate situational awareness, maintain compliance with international law, and retain the ability to dictate the tempo of modern conflict, DoD leadership must aggressively address the following methodological gaps.

9.1 Shift Investment Priorities from Platforms to Architectures

The acquisition focus must widen significantly from the procurement of individual, attritable drone platforms to the procurement of the underlying software, data pipelines, and sensing architectures. A swarm of 10,000 highly advanced drones is entirely neutralized if the enterprise cannot process their telemetry or conduct BDA in a severely jammed environment. Investment should heavily prioritize the development of ultra-fast neural networks, neuromorphic computing, and multi-modal sensor fusion algorithms (specifically integrating SAR, EO, and IR) that operate reliably at the tactical edge.⁹ The software that assesses the strike is as vital as the hardware that delivers it.

9.2 Establish Composite Formations to Reduce Sensor-to-Shooter Latency

Operational latency expands unacceptably when detection systems, kinetic shooters, EW cells, and BDA analysts operate in separate, stovepiped organizational stacks.²² The DoD must develop composite formations that co-locate and institutionalize the integration of these complementary capabilities at the brigade and battalion levels.²² Drone defense and employment cannot be siloed exclusively to dedicated air defense or aviation units; every unit must possess organic, integrated capabilities to launch, assess, and iterate upon unmanned strikes.³

9.3 Codify Autonomous BDA Methodologies in Doctrine

Joint Publication 3-60 and supporting multi-service tactics, techniques, and procedures must be comprehensively revised to reflect the realities of the modern, automated battlefield.¹⁸ Doctrine must move beyond the centralized, human-dependent Phase I-III BDA processes and formally establish frameworks for automated, probabilistic edge assessment. Furthermore, doctrine must establish clear, standardized guidelines for when a commander is authorized to rely on AI-generated BDA to approve follow-on fires, explicitly addressing the inherent risks of algorithmic deception and false positives.

9.4 Mandate Systemic Traceability and Forensic Logging

To resolve the ethical and legal ambiguities surrounding massed autonomous strikes, the DoD must implement strict, non-negotiable enterprise requirements for data logging. Every drone within a deployed swarm must act as a distinct node that continuously records its sensor inputs, target selections, and BDA conclusions.³³ This methodology ensures that kinetic effects can be accurately attributed, AI behaviors can be audited post-mission, and compliance with the Law of Armed Conflict can be rigidly maintained, even when the human operator is no longer present in the immediate tactical loop.

By aggressively addressing these systemic requirements to design, build, operate, and evolve the BDA enterprise, the Department of Defense can successfully transform massed drone swarms from a blunt instrument of attrition into a highly precise, intelligent, and strategically decisive capability for the future Joint Force.

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Sources Used

1. Implementing DoD Replicator Initiative at Speed and Scale – Defense Innovation Unit, accessed April 24, 2026, https://www.diu.mil/latest/implementing-the-department-of-defense-replicator-initiative-to-accelerate
2. The Replicator initiative is key to the Army’s modernization | Brookings, accessed April 24, 2026, https://www.brookings.edu/articles/the-replicator-initiative-is-key-to-the-armys-modernization/
3. Countering the Swarm – CNAS, accessed April 24, 2026, https://www.cnas.org/publications/reports/countering-the-swarm
4. Air Force Doctrine Publication 3-60, Targeting, accessed April 24, 2026, https://www.doctrine.af.mil/Portals/61/documents/AFDP_3-60/3-60-AFDP-TARGETING.pdf
5. Countering Swarms: Strategic Considerations and Opportunities in …, accessed April 24, 2026, https://ndupress.ndu.edu/Joint-Force-Quarterly/Joint-Force-Quarterly-107/Article/Article/3197193/countering-swarms-strategic-considerations-and-opportunities-in-drone-warfare/
6. Unmanned Aerial Systems Intelligent Swarm Technology – RAND, accessed April 24, 2026, https://www.rand.org/content/dam/rand/pubs/research_reports/RRA2300/RRA2380-1/RAND_RRA2380-1.pdf
7. Beyond The Count: BDA For Modern Warfare – from MIPB, accessed April 24, 2026, https://mipb.ikn.army.mil/issues/jul-dec-2025/beyond-the-count/
8. Lethal Autonomous Weapon Systems (LAWS): Accountability, Collateral Damage, and the Inadequacies of International Law – Temple iLIT, accessed April 24, 2026, https://law.temple.edu/ilit/lethal-autonomous-weapon-systems-laws-accountability-collateral-damage-and-the-inadequacies-of-international-law/
9. Drone Swarm Detection Using Artificial Intelligence Based on Ultrafast Neural Networks, accessed April 24, 2026, https://armysbir.army.mil/topics/drone-swarm-detection-ai-based-ultrafast-neural-networks/
10. Hybrid learning framework for synergistic fusion of SAR and optical UAV data in wildfire surveillance – PMC, accessed April 24, 2026, https://pmc.ncbi.nlm.nih.gov/articles/PMC12669746/
11. Defining Swarm: A Critical Step Toward Harnessing the Power of Autonomous Systems, accessed April 24, 2026, https://www.armyupress.army.mil/journals/military-review/online-exclusive/2025-ole/defining-swarm/
12. DOD Innovation Official Discusses Progress on Replicator – Department of War, accessed April 24, 2026, https://www.war.gov/News/News-Stories/Article/Article/3999474/dod-innovation-official-discusses-progress-on-replicator/
13. Drone Swarms: The Potential AI Future of Drone Warfare – Small Wars Journal, accessed April 24, 2026, https://smallwarsjournal.com/2026/03/31/drone-warfare-ukraine-ai-swarms/
14. The Enduring Role of Fires on the Modern Battlefield – CSIS, accessed April 24, 2026, https://www.csis.org/analysis/chapter-6-enduring-role-fires
15. Unmanned Aircraft and the Revolution in Operational Warfare – Army University Press, accessed April 24, 2026, https://www.armyupress.army.mil/Journals/Military-Review/English-Edition-Archives/July-August-2025/Unmanned-Aircraft-Revolution/
16. Ukraine’s Future Vision and Current Capabilities for Waging AI-Enabled Autonomous Warfare – CSIS, accessed April 24, 2026, https://www.csis.org/analysis/ukraines-future-vision-and-current-capabilities-waging-ai-enabled-autonomous-warfare
17. Armed uninhabited aerial vehicles and the challenges of autonomy – The International Institute for Strategic Studies, accessed April 24, 2026, https://www.iiss.org/globalassets/media-library—content–migration/files/research-papers/armed-uninhabited-aerial-vehicles-and-the-challenges-of-autonomy.pdf
18. JP 3-60, Joint Targeting – Just Security, accessed April 24, 2026, https://www.justsecurity.org/wp-content/uploads/2015/06/Joint_Chiefs-Joint_Targeting_20130131.pdf
19. Joint Publication 3-60 – Executive Services Directorate, accessed April 24, 2026, https://www.esd.whs.mil/Portals/54/Documents/FOID/Reading%20Room/Joint_Staff/21-F-0520_JP_3-60_9-28-2018.pdf
20. Drones Aren’t Swarming Yet — But They Could – War on the Rocks, accessed April 24, 2026, https://warontherocks.com/drones-arent-swarming-yet-but-they-could/
21. Mass Precision Strike: Designing UAV Complexes for Land Forces – RUSI, accessed April 24, 2026, https://static.rusi.org/mass-precision-strike-final.pdf
22. Composite Air Defense Artillery Formations: Converging Non-Kinetic and Kinetic Capabilities – Line of Departure, accessed April 24, 2026, https://www.lineofdeparture.army.mil/Journals/Air-Defense-Artillery/ADA-Archive/2026-E-Edition/Composite-Air-Defense/
23. Breaking the Shield: Countering Drone Defenses – NDU Press, accessed April 24, 2026, https://ndupress.ndu.edu/Media/News/News-Article-View/Article/3838997/breaking-the-shield-countering-drone-defenses/
24. DE Weapons, Projectiles, Damage – DRONE DELIVERY OF CBNRECy – New Prairie Press Open Book Publishing, accessed April 24, 2026, https://kstatelibraries.pressbooks.pub/drone-delivery/chapter/9-kinetic-energy-weapons/
25. Eyes across the spectrum: Advancing India’s EO/IR Capabilities, accessed April 24, 2026, https://www.ey.com/content/dam/ey-unified-site/ey-com/en-in/insights/aerospace-defense/2025/ey-eyes-across-the-spectrum-advancing-india-s-eo-ir-capabilities.pdf
26. Drone-Based Wildfire Detection with Multi-Sensor Integration – MDPI, accessed April 24, 2026, https://www.mdpi.com/2072-4292/16/24/4651
27. Intelligent Firefighting Technology for Drone Swarms with Multi-Sensor Integrated Path Planning: YOLOv8 Algorithm-Driven Fire Source Identification and Precision Deployment Strategy – MDPI, accessed April 24, 2026, https://www.mdpi.com/2504-446X/9/5/348
28. Monitoring and Cordoning Wildfires with an Autonomous Swarm of Unmanned Aerial Vehicles – MDPI, accessed April 24, 2026, https://www.mdpi.com/2504-446X/6/10/301
29. An inside look at drone swarm behavior – McKelvey School of Engineering – WashU, accessed April 24, 2026, https://engineering.washu.edu/news/2026/An-inside-look-at-drone-swarm-behavior.html
30. Data Processing for Drones & Unmanned Systems, accessed April 24, 2026, https://www.unmannedsystemstechnology.com/expo/drone-data-processing/
31. Real-Time Disaster Response with AI Drone Swarms – Folio3 AI, accessed April 24, 2026, https://www.folio3.ai/blog/ai-drone-swarms-disaster-response
32. How Artificial Intelligence Could Reshape Four Essential Competitions in Future Warfare – RAND, accessed April 24, 2026, https://www.rand.org/content/dam/rand/pubs/research_reports/RRA4300/RRA4316-1/RAND_RRA4316-1.pdf
33. A Comprehensive Approach to Countering Unmanned Aircraft Systems – Joint Air Power Competence Centre, accessed April 24, 2026, https://www.japcc.org/wp-content/uploads/A-Comprehensive-Approach-to-Countering-Unmanned-Aircraft-Systems.pdf
34. Fusing Data into a Battle Damage Assessment for the Commander – U.S. Army, accessed April 24, 2026, https://api.army.mil/e2/c/downloads/2023/01/31/cb115ad9/22-732.pdf
35. Capabilities and Limitations of Real-Time Battle Damage Assessment – DTIC, accessed April 24, 2026, https://apps.dtic.mil/sti/pdfs/ADA420587.pdf
36. Loitering Munitions 101: What They Are and Why They Matter – IDGA, accessed April 24, 2026, https://www.idga.org/command-and-control/articles/loitering-munitions-101-what-they-are-why-they-matter
37. How AI is rewriting the rules of modern warfare – Vision of Humanity, accessed April 24, 2026, https://www.visionofhumanity.org/how-ai-is-rewriting-the-rules-of-modern-warfare/
38. UAV swarm communication and control architectures: a review, accessed April 24, 2026, https://cdnsciencepub.com/doi/10.1139/juvs-2018-0009
39. Scaling an Enterprise Drone Program for Future Success, accessed April 24, 2026, https://enterprise.dronenerds.com/blog/uncategorized/scaling-an-enterprise-drone-program-for-future-success/
40. Libya, The Use of Lethal Autonomous Weapon Systems – How does law protect in war?, accessed April 24, 2026, https://casebook.icrc.org/case-study/libya-use-lethal-autonomous-weapon-systems
41. Effects of AI-Enhanced Decision-Making on Air Force Doctrine – Air University, accessed April 24, 2026, https://www.airuniversity.af.edu/Wild-Blue-Yonder/Articles/Article-Display/Article/3828212/effects-of-ai-enhanced-decision-making-on-air-force-doctrine/

1. Executive Summary

The United States Department of Defense (DoD) is actively pursuing a fundamental paradigm shift in its approach to force projection. Driven by the imperative to offset the mass and capacity advantages of near-peer adversaries, the DoD has prioritized the rapid acquisition and fielding of thousands of all-domain attritable autonomous (ADA2) systems.¹ Initially operationalized through the Replicator initiative and subsequently evolving into the broader, heavily funded Defense Autonomous Warfare Group (DAWG) ³, this strategic vector seeks to overwhelm adversary anti-access/area-denial (A2/AD) networks using low-cost, expendable platforms.¹ However, the prevailing discourse surrounding mass unmanned aerial systems (UAS) operations suffers from a severe analytical blind spot: an overwhelming fixation on the digital, aerodynamic, and software-defined capabilities of the platforms, coupled with a systemic disregard for the physical logistics required to project them into a contested theater of operations.

Attritable systems are frequently conceptualized by defense planners as intangible, software-driven assets. In reality, fielding thousands of uncrewed platforms generates a colossal, highly sensitive, and dangerous physical footprint. This report outlines the systemic logistical requirements and constraints that dictate the feasibility of mass drone operations. The analysis reveals that the primary bottlenecks to these initiatives will not be autonomous swarming software or airframe manufacturing capacity, but rather the severe volumetric inefficiency of shipping fragile electronics, the stringent regulatory constraints governing the global transport of Class 9 hazardous lithium-ion batteries, and the immense power generation and climate-controlled storage requirements placed on austere forward operating bases.

Leadership must recognize that a drone’s operational weight is entirely distinct from its logistical weight. Its protective packaging, associated launch systems, and ground support equipment multiply its footprint exponentially. Furthermore, due to mandatory aviation transport regulations requiring lithium batteries to be shipped at a state of charge (SOC) below 30% ⁵, these platforms arrive at the tactical edge effectively incapacitated. This dynamic shifts the burden of energy generation directly to forward units, demanding industrial-scale charging infrastructure that relies heavily on vulnerable Class III bulk fuel supply chains.⁶

To ensure that thousands of ADA2 platforms can reliably reach and operate within contested environments, DoD planning must pivot from a platform-centric acquisition model to a logistics-first sustainment architecture. The ability to mass autonomous forces is entirely contingent on the United States Transportation Command (USTRANSCOM), the Military Sealift Command (MSC), and the tactical energy networks of deployed units.⁷ This report provides a comprehensive overview of the physical, regulatory, and infrastructural realities that currently threaten to throttle the deployment of mass autonomy.

2. The Strategic Context of Mass Autonomy and the Illusion of Scale

The modern battlefield is undergoing a rapid evolution, driven by the proliferation of networked, autonomous, and semi-autonomous systems. The Replicator initiative, launched in 2023 by the Defense Innovation Unit (DIU), represents a deliberate endeavor to integrate commercial-scale autonomous production with military operations.² The first iteration, Replicator 1, focuses on fielding thousands of aerial, ground, and maritime platforms by late 2025, while Replicator 2 pivots toward countering small unmanned aerial systems (C-sUAS).¹⁰ Selected platforms for these initial tranches include AeroVironment’s Switchblade 600, Anduril’s Altius-600, and the Ghost-X.²

To sustain and expand these efforts, the DoD has transitioned the underlying principles of Replicator into the Defense Autonomous Warfare Group (DAWG), signaling a massive financial commitment with nearly $55 billion allocated for research, development, and procurement in the coming fiscal cycles.³ The strategic appeal of these systems lies in their classification as “attritable”—platforms engineered and manufactured affordably enough that combatant commanders can tolerate a much higher degree of risk in their tactical employment.⁴

2.1 The Divergence Between Manned and Unmanned Logistics

The concept of attritability, while operationally advantageous, creates a psychological disconnect regarding logistics. Because the platforms are intended to be lost in combat ², there is a pervasive assumption that their supply chain is equally frictionless and expendable. This is a fundamental fallacy. An attritable drone requires the exact same meticulous supply chain handling, climate controls, and hazardous material processing as a non-attritable, multi-million-dollar precision-guided munition.

When procuring conventional manned aircraft, the DoD heavily scrutinizes the logistics tail. Platforms like the MQ-9 Reaper, which has amassed over two million flight hours, are supported by deeply entrenched, highly evolved logistical networks featuring dedicated runways, sophisticated hangars, and predictable maintenance schedules.¹³ Crucially, manned systems and large medium-altitude long-endurance (MALE) drones self-deploy; they fly from their point of origin to the theater of operations.

Attritable tactical drones, conversely, are classified as cargo. They do not fly to the fight; they must be boxed, palletized, trucked, flown via strategic airlift, offloaded, and distributed via tactical ground vehicles. Consequently, procuring a fleet of 10,000 small drones imposes a fundamentally different, and arguably more complex, strain on the Defense Transportation System (DTS) than sustaining a squadron of manned fighters.¹⁴ If the DoD attempts to scale drone procurement without proportionally scaling the physical infrastructure required to transport, store, and power them, the result will be localized logistical paralysis. Pallets of drones will inevitably become stranded at aerial ports of embarkation (APOEs) due to hazard restrictions, or they will arrive at forward bases that lack the electrical capacity to charge them.

3. Volumetric Inefficiency: Airframes, Fragility, and Packaging Standards

The most immediate physical constraint of mass drone deployment is the mathematical relationship between the drone’s operational dimensions and its required shipping volume. Modern tactical drones are meticulously optimized for aerodynamics and payload capacity, resulting in lightweight, fragile, and often awkwardly shaped airframes. To survive the extreme rigors of the military supply chain—which includes extreme temperature fluctuations, moisture, vibration, mechanical shock, and rough terrain handling—these systems must be packaged according to stringent, unyielding military specifications.

3.1 MIL-STD-2073-1E and the Reality of Level A Packing

The preservation, packaging, packing, and marking of military supplies are governed by(https://quicksearch.dla.mil/qsDocDetails.aspx?ident_number=37232), which dictates the methods required to protect materiel against environmentally induced degradation during multiple handling events in the DTS.¹⁴ Tactical drones, categorized as highly sensitive electronics with low fragility factors (frequently rated at less than 50 Gs of shock tolerance), require Level A military packing.¹⁶ Level A is the highest level of protection, mandated for items intended for long-term storage or deployment in austere, wartime environments.

Under these standards, a bare drone cannot simply be placed in a standard cardboard box. Level A packaging requires that the item be placed in individual, non-metallic inner packaging.¹⁸ This inner layer must be surrounded by specific cushioning material—such as foam-in-place (FIP) polyurethanes or specialized fast-pack inserts (PPP-B-1672)—that is non-combustible, electrically non-conductive, and highly absorbent.¹⁶ Furthermore, the entire cushioned assembly is often sealed within waterproof and vapor-proof barrier bags before being secured inside robust exterior shipping containers, such as wood-cleated panelboard boxes (ASTM-D-6251) or heavy-duty reusable molded containers.¹⁷

This mandatory preservation process creates massive volumetric inefficiency. A tactical drone’s weight is relatively negligible, but its “cube”—the cubic volume of its compliant shipping crate—is massive. The military logistics enterprise operates on the physical limitations of pallets and containers, and drones consume this space at an alarming rate.

3.2 Platform Loadout Metrics and the All-Up Round

Examining the specific physical dimensions of the platforms selected for the initial phases of the Replicator initiative illustrates this volumetric trap:

• AeroVironment Switchblade 600: This extended-range loitering munition is designed for precision strikes against armored targets.²² The bare munition itself weighs 15 kg (33 lbs) and has a length of 1.3 meters (51 inches).²² However, the Switchblade is shipped and deployed as an All-In-One Tube-Launched System. The All-Up Round (AUR), which includes the protective launcher tube and integrated firing hardware, weighs 29.5 kg (65 lbs).²² The Level A packaging required to protect this 1.3-meter AUR further increases the gross weight and significantly expands the volume.
• Anduril Altius-600: The ALTIUS-600 has a length of 1 meter and a base weight of 12.2 kg (27 lbs).²⁵ It is deployed from a pneumatic launch container.²⁶ While the airframe is lightweight, the rigid launch tube and the necessary foam-in-place cushioning demand substantial cargo space.¹⁹
• Anduril Ghost-X: Selected for the Army’s Company Level Small Unmanned Aircraft System (sUAS) Directed Requirement ²⁷, this system provides expeditionary surveillance. While highly capable, its complex rotor systems and delicate optics require extensive physical protection during transit to prevent misalignment.

When Air Force loadmasters build standard 463L pallets for strategic airlift, they are constrained by a usable base of 104 by 84 inches and a maximum height of 96 inches. Because drone crates cannot be stacked infinitely due to crush hazards and delicate center-of-gravity constraints, a single 463L pallet that could theoretically hold 10,000 pounds of dense artillery ammunition or water might only hold a few dozen attritable drones weighing a fraction of that amount. The DoD is effectively consuming its most premium strategic transportation asset to fly empty space and protective foam across the ocean.

4. The Class 9 Hazard: Lithium Battery Transport Regulations

While volumetric inefficiency restricts the amount of cargo space available, lithium-ion batteries present an acute, hard-stop regulatory constraint that dictates how, when, and if these platforms can be moved at all.

Every modern electric tactical UAS relies on high-energy-density lithium-ion or lithium-polymer batteries to achieve necessary flight times and payload capacities.²⁸ Under both international civilian law and strict military regulations, lithium batteries are universally classified as Class 9 Hazardous Materials.³⁰ Depending on their configuration, they are categorized as UN3480 (for standalone lithium-ion batteries) or UN3481 (for lithium-ion batteries packed with or contained in equipment).³² The transportation of these assets is heavily scrutinized and restricted due to the severe risk of thermal runaway—a catastrophic internal short-circuit chain reaction that causes intense, self-sustaining fires that are highly resistant to standard aviation fire suppression systems.³³

4.1 Air Transport Restrictions and AFMAN 24-204

The strategic airlift of these batteries is governed by a complex web of overlapping authorities, primarily the International Air Transport Association (IATA) Dangerous Goods Regulations and the Air Force Joint Manual (AFMAN 24-204), “Preparing Hazardous Materials for Military Air Shipment”.⁵

To mitigate the existential risk of an in-flight thermal runaway event, current regulations mandate that rechargeable lithium batteries must be shipped at a State of Charge (SOC) not exceeding 30% of their rated capacity.⁵ Furthermore, there are stringent limits on the maximum net quantity of lithium batteries permitted per cargo aircraft compartment.³³ For certain configurations and sizes, the maximum net quantity per cargo aircraft can be as low as 35 kg.³¹ While waivers and exceptions exist for national security movements under 49 CFR 173.7, the baseline safety protocols dictate severe segregation and quantity limits to ensure that an oxygen-starved cargo hold or automated fire suppression system can actually contain a potential blaze.³³

This regulatory environment creates a profound logistical bottleneck for the mass deployment envisioned by the Replicator initiative:

1. Compartment Saturation: A C-17 Globemaster III cannot simply be filled floor-to-ceiling with attritable drones. Load planners must meticulously distribute the UN3480/UN3481 hazardous materials across different isolated cargo compartments to avoid exceeding strict Class 9 net quantity limits.³³ Consequently, if a specific drone model carries a heavy battery payload for extended endurance, the aircraft may “hazmat out” (reach its legal hazardous material weight limit) while the physical cargo bay remains largely empty.
2. Dead on Arrival Logistics: Because batteries must legally and safely be shipped at less than 30% SOC ⁵, drones arriving in the theater of operations are not combat-ready. They cannot be rapidly offloaded from a transport aircraft and immediately launched to counter an advancing adversary. They must first be routed through a logistical node, unpacked, and fully recharged. This operational reality completely transfers the burden of operational readiness directly onto the theater’s tactical power grid, introducing devastating delays to force projection timelines.

4.2 Packaging Integrity and Retrograde Complexities

The dangers of Class 9 materials are amplified when dealing with damaged systems. If an attritable drone is damaged during transit, rough handling, or limited operations and requires retrograde transport for depot-level repair or forensic analysis, the battery must be isolated. Damaged or defective batteries face even stricter protocols, requiring individual non-metallic inner packaging surrounded by non-combustible, electrically non-conductive cushioning, with explicit exterior markings denoting the heightened hazard.¹⁸ Furthermore, it is strictly prohibited to mix hazardous and non-hazardous solid waste in the same package.⁵ Managing this retrograde process across thousands of deployed systems drastically complicates reverse logistics, requiring forward units to act as highly trained hazardous material processing centers. The Commercial Vehicle Safety Alliance (CVSA) has even recommended that the Department of Transportation reclassify lithium batteries from Class 9 to a more restrictive Division 4.3 material due to these runaway thermal reaction risks, which would further tighten future airlift and ground transport requirements.³⁷

5. Strategic Airlift and Sealift Constraints

The ability to successfully mass autonomous forces is entirely contingent on the capacity and readiness of the United States Transportation Command (USTRANSCOM). The physical realities of volumetric packaging and Class 9 hazardous materials translate directly into severe, structural strain on strategic mobility assets.

5.1 The Strategic Airlift Deficit

USTRANSCOM relies on a validated requirement of a 275-aircraft organic strategic airlift fleet to meet national defense objectives and global contingency plans.⁸ The C-17 Globemaster III serves as the backbone of this fleet, providing rapid, inter-theater mobility. However, strategic airlift is fundamentally designed and optimized for high-value, high-density, time-sensitive cargo.

When the DoD demands the rapid, simultaneous deployment of thousands of high-cube, low-density attritable drones—each packed in expansive protective crates and subject to compartment-specific lithium battery limits—the airlift architecture is forced to operate at maximum inefficiency. In a crisis scenario, drones will compete directly for premium pallet space against critically needed precision munitions, medical supplies, and ground vehicle repair parts. In a contested logistics environment, where speed equates directly to deterrence ⁸, dedicating vast swaths of C-17 capacity to transport empty space and packing foam represents an unacceptable tactical trade-off.

Intra-theater lift faces similar structural pressures. The Air Force’s retirement of older C-130H aircraft has reduced the tactical airlift fleet from over 500 aircraft in 2003 to a congressionally mandated inventory of 271.⁸ Distributing massive quantities of volumetric drone crates from major theater hubs to dispersed forward operating bases using a constrained C-130 fleet will inevitably result in operational delays. While innovative concepts like the Rapid Dragon program—which successfully demonstrated the deployment of palletized munitions directly from C-17 and EC-130 aircraft ³⁸—show promise for direct aerial delivery, these systems still consume vast amounts of cargo volume and require extensive rigging.

5.2 The Atrophy of Strategic Sealift

Historically, when airlift capacity is constrained or reserved for immediate priorities, the DoD relies heavily on the Military Sealift Command (MSC) to transport approximately 90 percent of U.S. Army and Marine Corps equipment into the theater of operations.⁹ For the true mass deployment of drone fleets, utilizing standard International Organization for Standardization (ISO) containers via sealift is the only mathematically viable method.

However, the strategic sealift enterprise is currently facing an unprecedented readiness crisis. Current assessments indicate that MSC readiness levels have dropped to an alarming 59 percent, driven primarily by vessel age and deteriorating material condition.⁹ The sealift fleet is projected to lose between 1 million and 2 million square feet of capacity annually as legacy ships reach the end of their useful service lives.⁹

Furthermore, in a pacing scenario against a near-peer adversary such as China, sea lines of communication (SLOCs) from the continental United States to the Indo-Pacific will be heavily contested.⁹ Transporting mass quantities of Class 9 lithium batteries via sealift also invokes the International Maritime Dangerous Goods (IMDG) Code, which mandates robust, fire-resistant packaging, adequate cushioning, and strict stowage segregation.⁵

The systemic requirement is unavoidable: The Replicator initiative cannot rely solely on the C-17 fleet for initial deployment. The DoD must urgently integrate mass drone packaging into standard ISO container dimensions—specifically utilizing TRICON (8’x8’x6.5′), BICON (8’x8’x10′), and QUADCON (8’x6.10’x4.9′) steel-framed containers ³⁹—that are engineered for hazardous material sealift, and combatant commanders must factor the extended transit times of maritime logistics into their operational plans.

6. Forward Operating Base Footprint: Storage and Climate Control

Upon successfully navigating the strategic airlift or sealift pipeline and reaching the theater of operations, the logistical burden transitions entirely from USTRANSCOM to the gaining tactical units. The pervasive assumption that thousands of attritable drones can simply be unloaded, unboxed, and stacked in a general-purpose, unconditioned supply tent completely ignores the volatile chemistry of lithium-ion technology and the fragility of the platforms.

6.1 The Aggregate Risk of Thermal Runaway

Aggregating thousands of lithium-ion batteries at a Forward Operating Base (FOB) introduces a profound vulnerability to the installation. A single thermal runaway event—whether caused by mechanical damage during rough transport, a latent manufacturing defect, or an enemy kinetic strike—can rapidly propagate to adjacent stored batteries. This creates an uncontrollable, self-sustaining chemical blaze that conventional firefighting techniques and standard water suppression systems cannot easily extinguish.³⁴

Military history provides stark precedents. The Navy’s Naval Surface Warfare Center (NSWC) Carderock Division has documented incidents where standard military lithium batteries, such as the widely used BB 2590, entered thermal runaway while stored in an Army vehicle-mounted shelter, causing massive damage to surrounding equipment and exposing personnel to severe hazard.³⁴

6.2 Specialized Climate-Controlled Infrastructure

To prevent spontaneous degradation, maintain operational capacity, and prevent thermal events, lithium-ion batteries must be stored in specific, highly regulated environmental conditions. Both industry standards and DoD best practices dictate that these batteries must be kept at stable temperatures, generally below 80°F (26.6°C).⁴¹ In austere, high-temperature operational environments—such as the Middle East or the Indo-Pacific during summer months—maintaining this temperature requires dedicated, power-hungry climate control systems running continuously.

Standard canvas tents or rudimentary plywood structures are entirely inadequate. Adequate storage requires purpose-built facilities, such as commercial DrumLoc buildings or the military’s specialized CLASSIC (Containerized Lithium-ion Battery Storage and Sustained Intelligent Charging) containers developed by NSWC.³⁴ These specialized hazardous material bunkers require robust, integrated safety features, including:

• Explosion-proof electrical accessories, switches, and interior lighting.
• Active clean-agent fire suppression devices (e.g., FM 200 systems) tailored for chemical fires.⁴¹
• Advanced sensors capable of detecting chemical off-gassing, temperature spikes, or smoke prior to a full thermal runaway event.³⁴
• Passive physical mitigation measures, such as internal blast walls, to prevent failure propagation between stored units and to direct the blast outward rather than upward into the facility.³⁴

Consequently, deploying a mass drone capability does not merely require runway space or a clear patch of dirt; it necessitates the deployment of heavy, specialized ISO containers acting as forward hazardous material bunkers, which in turn require constant, uninterrupted power to run their HVAC and automated sensor systems.

7. Industrial-Scale Power Generation at the Tactical Edge

The most critical, yet systematically overlooked, operational requirement of mass drone deployment is tactical power generation. As previously established, drones arrive in theater at less than 30% SOC due to strict aviation transport regulations.⁵ Before a single swarm can be launched to achieve the mass effects envisioned by Replicator, the entire fleet must be charged. This transforms a forward drone unit into an industrial power consumer.

7.1 The Mathematics of Megawatt Demand

Commercial and military drone operations are exceptionally energy-intensive. A single tactical drone team conducting persistent intelligence, surveillance, and reconnaissance (ISR) or kinetic strike operations can easily cycle through 10 to 12 battery charges per day, consuming approximately 2 to 3 kilowatt-hours (kWh) of electricity daily.⁴² Scaling this baseline to the DoD’s vision of fielding “multiple thousands” of autonomous platforms ⁴ creates a staggering localized power demand.

If a combatant commander intends to launch a coordinated wave of 1,000 drones within a narrow operational window, those batteries must be charged simultaneously. Fast-charging a single heavy-lift or long-range tactical drone battery requires a dedicated draw of between 150W and 300W of continuous power.⁴³ In parallel, the necessary ground support equipment—including operator laptops, network routers, data relays, and GPS base stations—draws a continuous 100W to 250W per station.⁴³

When operating multiple systems simultaneously during pre-mission staging, the peak electrical demand rapidly surges into the tens of thousands of watts per tactical node.⁴³ Standard consumer-grade portable power stations, small solar arrays, or vehicle-mounted inverters are vastly insufficient for this industrial scale.

7.2 The Vulnerability of Tactical Generators and Class III Logistics

Historically, the default solution to remote, off-grid power demand has been the towed gasoline or diesel generator.⁶ However, relying on traditional internal combustion generators to power mass drone operations presents severe tactical liabilities that undermine the very purpose of the capability:

1. Acoustic and Thermal Signatures: In an era of advanced multi-spectral ISR, the massive noise pollution and intense thermal bloom of a large generator farm immediately compromise the position of the drone launch site.⁶ Adversary sensors will detect the power generation node long before the drones are launched, inviting preemptive kinetic strikes.
2. Vibration Interference: Micro-vibrations emanating from heavy diesel generators can interfere with the delicate calibration of drone targeting optics and sensitive charging equipment, leading to high failure rates before takeoff.⁶
3. Contested Class III Logistics: Generators burn vast quantities of fuel. Moving thousands of gallons of Class III bulk fuel to remote launch sites requires vulnerable, highly visible convoy operations. This reliance on a heavy logistics tail defeats the strategic purpose of utilizing distributed, low-risk attritable forces.

7.3 The Hazards of Parallel Charging

To save time and meet aggressive operational tempos, drone operators frequently utilize parallel charging—connecting multiple lithium-polymer (LiPo) batteries to a single high-output charger via a parallel charging board.⁴⁵ While highly efficient for rapid turnarounds, parallel charging introduces acute fire risks if not managed with absolute precision.

Batteries connected in parallel must possess the identical cell count and very similar starting voltages (typically within 0.1V of each other).⁴⁵ If a depleted battery is hastily connected in parallel with a partially charged battery, the voltage differential causes a massive, uncontrolled rush of current into the depleted battery, frequently resulting in catastrophic cell failure, explosions, and fires.⁴⁷ Furthermore, charging at higher currents (e.g., 2c instead of the safer standard 1c rate) drastically increases the wear on the battery and the risk of thermal events.⁴⁸ Managing this delicate, mathematically precise charging process across thousands of rapidly degrading attritable batteries in a chaotic combat environment requires sophisticated Battery Management Systems (BMS) ²⁹ and highly trained personnel, which inherently slows the tempo of operations.

8. Maintenance Footprint, Personnel, and Training Readiness

The very term “attritable” implies expendability and a short lifecycle, which often leads to the dangerous assumption that these platforms require little to no maintenance or human support. In reality, assembling, calibrating, launching, and managing a fleet of attritable UAS requires a highly specialized human capital footprint and expansive physical facilities.

8.1 Assembly and Facility Square Footage

Most tactical drones, to save volumetric space during strategic airlift, are shipped partially disassembled within their protective MIL-STD crates.⁴⁹ Upon arrival at the FOB, they must be meticulously unpacked, assembled, firmware-updated, and flight-checked before they can be assigned to a mission. Establishing a forward drone assembly and maintenance facility requires significant physical space that must be factored into base planning.

Basic institutional standards for drone laboratories and maintenance facilities dictate a minimum of 750 square feet solely for assembly and maintenance areas, with 10-to-12-foot ceilings to accommodate wingspan clearances and component testing.⁵⁰ Storage rooms capable of holding just 500 drones require upwards of 1,000 square feet of dedicated, secure shelving.⁵⁰ When scaling to the DAWG and Replicator goal of multiple thousands of systems, commanders will require massive, semi-permanent structures—such as large clamshell tents or repurposed aircraft hangars—simply to process the unboxing and assembly of the hardware. This vast physical requirement directly contradicts the operational goal of maintaining a light, agile, and geographically dispersed expeditionary footprint.⁵¹

8.2 The Human Capital Constraint

Unmanned systems, paradoxically, are highly manpower-intensive on the ground. A complex UAV operation often requires at least seven crewmembers dedicated to specific tasks: takeoff and landing procedures, in-flight monitoring, payload operation, and flight line maintenance.⁵² While the Replicator initiative explicitly aims to leverage advanced autonomy to allow a single operator to control multiple vehicles in a swarm configuration ¹, the physical handling, battery swapping, and maintenance of the drones remains a heavily manual task.

To manage the unprecedented battery and maintenance logistics, the DoD will need to fundamentally restructure its forward support companies (FSCs) and sustainment brigades.⁵³ Battlefield energy generation and distribution nodes must be established within Light Support Battalions (LSB) and Division Sustainment Support Battalions (DSSB).⁷ This shift requires existing 91D (Generator Mechanic) and 94-series personnel to undergo extensive retraining to manage complex hybrid and lithium-ion systems, diagnosing battery health and managing parallel charging racks.⁷

Furthermore, training the sheer number of operators required to employ thousands of drones demands a massive expansion of the institutional training base. Simulator training is essential for building initial flight proficiency and mitigating crash risks.⁵⁴ The Marine Corps, for example, is heavily reliant on enterprise-resourced simulation capabilities delivered via the Marine Common Virtual Platform (MCVP)—such as DART 2.0 and FlowState—as well as commercial simulators like Velocidrone, to provide service-wide training solutions.⁵⁴ Scaling this training pipeline to match the procurement of the hardware is a multi-year endeavor.

8.3 Supply Chain Security and Parts Replacement

Finally, forward units cannot simply rely on localized procurement or commercial replacement of broken drone parts to sustain operations. Due to strict supply chain security mandates, such as the Federal Acquisition Supply Chain Security Act (FASC), there is a blanket prohibition on the use of FASC-prohibited unmanned aircraft systems and associated elements.⁵⁵ This legislation ensures that no components sourced from adversarial nations (such as certain Chinese-manufactured motors or flight controllers) can be integrated into DoD networks. Consequently, every spare propeller, servo, and circuit board must be sourced through secure, vetted, and often severely backlogged military supply chains. This reality forces deployed units to stockpile vast quantities of authorized spare parts at the FOB to maintain readiness, further increasing the logistical cube and storage requirements.

9. Strategic Conclusions and Required Leadership Action

The United States Department of Defense possesses the unparalleled technological prowess to design, develop, and manufacture thousands of highly capable autonomous systems. The massive financial commitments to the DAWG and Replicator initiatives guarantee that the industrial base will produce the hardware. However, the true measure of mass autonomy’s success will not be determined by factory output or lines of code, but by the Defense Transportation System’s ability to project those assets globally without buckling under the weight of archaic packaging standards, hazardous material laws, and localized power deficits.

To ensure that mass drone operations transition from a theoretical strategic concept to a viable, reliable tactical reality, leadership must immediately acknowledge and aggressively mitigate the physical logistics footprint. The analysis indicates several critical areas for immediate, systemic action:

1. Redesign Military Packaging for Drones: The DoD must collaborate directly with defense contractors to engineer MIL-STD-2073 compliant shipping configurations that drastically reduce the “cube.” Drones should be designed with foldable, robust components that minimize the need for expansive foam-in-place cushioning, maximizing the density of a 463L pallet and ISO containers. The packaging must be considered as important as the payload.
2. Modernize the Class 9 Hazardous Pipeline: USTRANSCOM and the Defense Logistics Agency (DLA) must develop streamlined, pre-approved hazardous material transport corridors specifically optimized for lithium-ion batteries. To bypass the airlift bottleneck, the DoD must invest heavily in specialized ISO containers (analogous to the CLASSIC system) that can transport, safely store, and simultaneously charge batteries at the tactical edge, relying more heavily on proactive strategic sealift.
3. Elevate Energy to a Primary Supply Class: The Brigade Support Operations (SPO) and unit S4s must immediately begin treating electrical power forecasting with the exact same rigor and priority as Class III (Fuel) and Class V (Ammunition) sustainment.⁷ The DoD must rapidly procure modular, silent, and high-capacity battlefield energy storage networks to decouple deployed drone units from vulnerable liquid fuel supply chains and noisy tactical generators.

The technology of mass autonomy is profound, and its potential to deter aggression is immense. Yet, it remains inextricably tethered to the physical world. By shifting the strategic focus toward the unglamorous realities of logistics, volumetric packaging, hazardous materials, and tactical power generation, DoD leadership can ensure that the autonomous systems built to win the next conflict are actually capable of reaching the battlefield.

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Sources Used

1. Replicator: A Bold New Path for DoD | Center for Security and Emerging Technology %, accessed April 24, 2026, https://cset.georgetown.edu/article/replicator-a-bold-new-path-for-dod/
2. Deep Dive: Pentagon’s Replicator Initiative Raises Questions | Inkstick, accessed April 24, 2026, https://inkstickmedia.com/deep-dive-pentagons-replicator-initiative-raises-questions/
3. Pentagon officials broadly detail $55 billion drone plan under DAWG – Breaking Defense, accessed April 24, 2026, https://breakingdefense.com/2026/04/pentagon-officials-broadly-detail-55-billion-drone-plan-under-dawg/
4. DOD Innovation Official Discusses Progress on Replicator > Department of Defense Manufacturing Technology Program > News Display, accessed April 24, 2026, https://www.dodmantech.mil/News/News-Display/Article/3999474/dod-innovation-official-discusses-progress-on-replicator/
5. Transportation – U.S. Army Batteries, accessed April 24, 2026, https://battery.army.mil/safety/transportation-safety/
6. Unleashing the Swarm: The Ultimate Guide to Professional Portable Power for Drone Operations – New Use Energy, accessed April 24, 2026, https://newuseenergy.com/blogs/news/unleashing-the-swarm-the-ultimate-guide-to-professional-portable-power-for-drone-operations
7. Best Practices on Operationalizing Battlefield Energy | Article | The United States Army, accessed April 24, 2026, https://www.army.mil/article/287897/best_practices_on_operationalizing_battlefield_energy
8. 1 Statement of General Randall Reed, United States Air Force Commander, United States Transportation Command Before the House Ar, accessed April 24, 2026, https://docs.house.gov/meetings/AS/AS28/20260318/119070/HHRG-119-AS28-20260318-SD004.pdf
9. The dangerous collapse of US strategic sealift capacity – The Strategist, accessed April 24, 2026, https://www.aspistrategist.org.au/the-dangerous-collapse-of-us-strategic-sealift-capacity/
10. DoD promised a ‘swarm’ of attack drones. We’re still waiting. – Responsible Statecraft, accessed April 24, 2026, https://responsiblestatecraft.org/replicator/
11. Pentagon’s Replicator Initiative Sets Sights on Counter-UAS – National Defense Magazine, accessed April 24, 2026, https://www.nationaldefensemagazine.org/articles/2024/12/16/pentagons-replicator-initiative-sets-sights-on-counteruas
12. Attritable Unmanned Aircraft Systems: Conceptualization and Key Players – DSIAC – dtic.mil, accessed April 24, 2026, https://dsiac.dtic.mil/state-of-the-art-reports/attritable-unmanned-aircraft-systems-conceptualization-and-key-players/
13. MQ-9A Passes 2 Million Flight Hours | General Atomics Aeronautical Systems Inc., accessed April 24, 2026, https://www.ga-asi.com/mq-9a-passes-2-million-flight-hours
14. Standard Practice for Military Packaging – ASSIST-QuickSearch Document Details – DLA, accessed April 24, 2026, https://quicksearch.dla.mil/qsDocDetails.aspx?ident_number=37232
15. afman 24-604 – Air Force – USAF, accessed April 24, 2026, https://static.e-publishing.af.mil/production/1/af_a4/publication/afman24-604/afman24-604.pdf
16. What Is MIL-STD-2073 Packaging? – Export Corporation, accessed April 24, 2026, https://www.exportcorporation.com/what-is-mil-std-2073-packaging/
17. MIL-STD-2073_1E_CHG-4.pdf – S3VI, accessed April 24, 2026, https://s3vi.ndc.nasa.gov/ssri-kb/static/resources/MIL-STD-2073_1E_CHG-4.pdf
18. 49 CFR 173.185 — Lithium cells and batteries. – eCFR, accessed April 24, 2026, https://www.ecfr.gov/current/title-49/subtitle-B/chapter-I/subchapter-C/part-173/subpart-E/section-173.185
19. The Basics – ASC Packaging Storage and Containerization Center – U.S. Army, accessed April 24, 2026, https://www.pscc.army.mil/Portals/92/Documents/PKG_01_Packaging%20_the_Basics.pdf?ver=jVqRtUlH0eGE9rfwrGlXnA%3D%3D
20. Military Spec Crates Explained – Valley Box Company, accessed April 24, 2026, https://www.valleybox.com/blog/military-spec-crates-explained
21. MIL-STD-2073-1 Exterior Shipping Containers – Camp Hill Logistics, accessed April 24, 2026, https://camphill.leidos.com/code_lookup.nsf/ESC?OpenPage
22. Switchblade® 600 – AeroVironment, accessed April 24, 2026, https://www.avinc.com/solution/switchblade-600/
23. AeroVironment Switchblade – Wikipedia, accessed April 24, 2026, https://en.wikipedia.org/wiki/AeroVironment_Switchblade
24. Switchblade® 600 Loitering Munition Systems | Kamikaze Drones | Suicide Drone | Tactical Missile Systems | AV – AeroVironment, accessed April 24, 2026, https://www.avinc.com/lms/switchblade-600
25. Anduril ALTIUS – Designation-Systems.Net, accessed April 24, 2026, https://www.designation-systems.net/dusrm/app4/altius.html
26. Taiwan Receives First Batch of U.S.-Made Altius 600M Drones, accessed April 24, 2026, https://militarnyi.com/en/news/taiwan-receives-first-batch-of-u-s-made-altius-600m-drones/
27. Ghost-X Selected for U.S. Army’s Company Level sUAS Directed Requirement | Anduril, accessed April 24, 2026, https://www.anduril.com/news/ghost-x-selected-for-u-s-army-s-company-level-suas-directed-requirement
28. The Study of Electrical Energy Power Supply System for UAVs Based on the Energy Storage Technology – MDPI, accessed April 24, 2026, https://www.mdpi.com/2226-4310/9/9/500
29. Drone (UAV) Battery Market Report 2025-2030 [287 Pages & 398 Tables], accessed April 24, 2026, https://www.marketsandmarkets.com/Market-Reports/drone-battery-market-131005766.html
30. Navigating State-Specific Regulations for Lithium-Ion Batteries – Americase, accessed April 24, 2026, https://www.americase.com/navigating-state-specific-regulations-for-lithium-ion-batteries/
31. Challenges in Transporting Lithium Batteries – Clip-Lok, accessed April 24, 2026, https://clip-lok.com/challenges-in-transporting-lithium-batteries/
32. Common Challenges in Battery Shipping and Solutions – FreightAmigo, accessed April 24, 2026, https://www.freightamigo.com/en/blog/logistics/common-challenges-in-battery-shipping-and-solutions/
33. Lithium Battery Guide for Shippers – Pipeline and Hazardous Materials Safety Administration, accessed April 24, 2026, https://www.phmsa.dot.gov/sites/phmsa.dot.gov/files/2024-11/Lithium-Battery-Guide-2024.pdf
34. CLASSIC Battery Container – Navsea, accessed April 24, 2026, https://www.navsea.navy.mil/Portals/103/Documents/Exhibits/SAS2022/1300-CLASSIC_BatteryContainer-Hays-20220404.pdf
35. 2024 LITHIUM BATTERY SHIPPING GUIDE – Hazmateam, accessed April 24, 2026, https://hazmateam.learningcart.com/uploads/2024LITHIUMBATTERIES/2024HAZMATEAMLITHIUMBATTERYSHIPPINGGUIDEINTERACTIVEJAN_1_2024.pdf
36. Hazardous Material, Part II, Chapter 204 – USTransCOM, accessed April 24, 2026, https://www.ustranscom.mil/dtr/part-ii/dtr_part_ii_204.pdf
37. April 22, 2025 Acting Administrator Kochman U.S. Department of Transportation Pipeline and Hazardous Materials Safety Administr – CVSA, accessed April 24, 2026, https://cvsa.org/wp-content/uploads/CVSA-Letter-to-PHMSA-Regarding-Lithium-Batteries-Recommendations.pdf
38. Rapid Dragon Demonstrates Palletized Munition Capability in First C-17 and EC-130 System-Level Demonstrations – Lockheed Martin, accessed April 24, 2026, https://news.lockheedmartin.com/rapid-dragon-demonstrates-palletized-munition-capability-in-first-C-17-and-EC-130-system-level-demonstrations
39. The Buyer’s Guide for Military Shipping Container – Mobile Modular Portable Storage, accessed April 24, 2026, https://www.mobilemodularcontainers.com/blog/military-shipping-containers
40. Appendix B – DEPARTMENT OF DEFENSE (DOD) INTERMODAL CONTAINER STANDARDS – USTransCOM, accessed April 24, 2026, https://www.ustranscom.mil/dtr/part-vi/dtr_part_vi_app_b.pdf
41. Lithium Ion Battery Storage Requirements, accessed April 24, 2026, https://www.uschemicalstorage.com/lithium-ion-battery-storage-requirements/
42. No. 26-1116, Powering The Front: Tactical Energy Delivery and Management in the Ukraine War – U.S. Army, accessed April 24, 2026, https://api.army.mil/e2/c/downloads/2026/03/30/c260713f/no-26-1116-powering-the-front-tactical-energy-delivery-and-management-in-the-ukraine-war.pdf
43. Drone Show Power Guide: How Many Watts Do You Really Need – EcoFlow, accessed April 24, 2026, https://www.ecoflow.com/us/blog/drone-show-power-requirements-guide
44. Power under pressure: Meeting the military’s surging energy demands, accessed April 24, 2026, https://militaryembedded.com/comms/power-electronics/power-under-pressure-meeting-the-militarys-surging-energy-demands
45. Mastering LiPo Parallel Charging: The Safety Guide for FPV Drone Pilots – Oscar Liang, accessed April 24, 2026, https://oscarliang.com/parallel-charging-multiple-lipo/
46. Charging Multiple Lithium-Polymer (Lipo) Batteries at once – Planet Geek!, accessed April 24, 2026, https://planet-geek.com/2017/07/09/drones/charging-multiple-lithium-polymer-lipo-batteries-at-once/
47. Is it safe to charge these different brands at the same time and how many amps should I use? – Reddit, accessed April 24, 2026, https://www.reddit.com/r/fpv/comments/12do8ue/is_it_safe_to_charge_these_different_brands_at/
48. At what current should I charge a LiPo battery? – Drones and Model Aircraft Stack Exchange, accessed April 24, 2026, https://drones.stackexchange.com/questions/971/at-what-current-should-i-charge-a-lipo-battery
49. MCO P4030.21D PACKAGING OF MATERIEL – Marines.mil, accessed April 24, 2026, https://www.marines.mil/portals/1/Publications/MCO%20P4030.21D.pdf
50. How to Set Up a Drone Lab | Equipment and Space Requirements – Robocraze, accessed April 24, 2026, https://robocraze.com/blogs/post/how-to-set-up-a-drone-lab-equipment-and-space-requirements
51. The fresh maintenance and sustainment challenges as UAVs take off in defense, accessed April 24, 2026, https://militaryembedded.com/unmanned/counter-uas/the-fresh-maintenance-and-sustainment-challenges-as-uavs-take-off-in-defense
52. Annotated Bibliography (1997 – 2021): Crew and Staffing Requirements of Unmanned Aircraft Systems in Air Carrier Operations – Federal Aviation Administration, accessed April 24, 2026, https://www.faa.gov/sites/faa.gov/files/2022-07/Annotated%20Bibliography%20(1997-2021)-%20Crew%20and%20Staffing%20Requirements%20of%20Unmanned%20Aircrafts%20Systems%20in%20Air%20Carrier%20Operations.pdf
53. 23-08-682-leader-s-guide-to-maintenance-and-services-aug-23-public.pdf – U.S. Army, accessed April 24, 2026, https://api.army.mil/e2/c/downloads/2023/09/29/c9a4e39d/23-08-682-leader-s-guide-to-maintenance-and-services-aug-23-public.pdf
54. APPROVED TRAINING REQUIREMENTS FOR SMALL UNMANNED AERIAL SYSTEMS > United States Marine Corps Flagship > Messages Display, accessed April 24, 2026, https://www.marines.mil/News/Messages/Messages-Display/Article/4366306/approved-training-requirements-for-small-unmanned-aerial-systems/
55. 52.240-1 Prohibition on Unmanned Aircraft Systems Manufactured or Assembled by American Security Drone Act-Covered Foreign Entities. | Acquisition.GOV, accessed April 24, 2026, https://www.acquisition.gov/far/52.240-1
56. M-26-02 Ensuring Government Use of Secure Unmanned Aircraft Systems and Supporting – The White House, accessed April 24, 2026, https://www.whitehouse.gov/wp-content/uploads/2025/11/M-26-02-Ensuring-Government-Use-of-Secure-Unmanned-Aircraft-Systems-and-Supporting-United-States-Producers.pdf

1. Executive Summary

The Department of Defense is currently executing a fundamental transformation in its approach to power projection, characterized by the accelerated acquisition and fielding of autonomous and unmanned systems. Initiatives designed to rapidly deploy All-Domain Attritable Autonomous platforms promise to provide combatant commanders with unprecedented capabilities in reconnaissance, surveillance, target acquisition, and precision strike operations.¹ The underlying strategic logic assumes that overwhelming adversaries with thousands of low-cost, expendable systems will neutralize advantages in traditional mass and conventional force structure.³ However, the strategic dialogue surrounding these platforms frequently isolates the technology from its physical sustainment requirements, generating a systemic blind spot. The widespread assumption that unmanned systems inherently reduce the logistics tail of a deployed force is a dangerous oversimplification that ignores the physical realities of global transport and sustainment.²

This report examines the systemic, physical logistics, and basing infrastructure requirements necessary to design, build, transport, operate, and sustain mass unmanned aerial systems in contested theaters. An analysis of the physical characteristics of current platforms indicates that the primary constraint in projecting mass drone operations is not weight, but volume.⁶ Unmanned aerial systems are exceptionally low-density cargo. They exhaust the volumetric capacity—the “cube”—of strategic airlift platforms long before reaching weight limits, fundamentally altering sortie generation calculations for the existing mobility fleet.⁶ The operational decision to package fragile airframes in protective shipping containers rather than standard logistics pallets drastically exacerbates this issue, imposing severe tare weight penalties that degrade overall airlift efficiency.⁷

Furthermore, the proliferation of battery-powered autonomous systems introduces severe hazardous materials storage and handling challenges.⁸ High-capacity lithium-ion and lithium-polymer batteries require specialized, climate-controlled environments to mitigate the risks of chemical degradation and catastrophic thermal runaway.⁹ The requirement to transport, store, and simultaneously charge thousands of these batteries at forward operating bases creates a massive, continuous demand for tactical electrical power.¹¹ This dynamic does not eliminate the military’s reliance on fossil fuels; rather, it shifts the logistical burden from aviation fuel to the massive quantities of diesel generation required to sustain tactical microgrids at the edge of the battlefield.¹¹

To ensure that the systems acquired under highly compressed fielding initiatives can physically reach the theater of operations and remain viable in distributed environments, defense leadership must recognize these underlying supply chain realities. Addressing the tyranny of volume, the volatility of lithium-based energy storage, the structural gaps in pre-positioned war reserve materiel, and the electrical demands of forward bases is essential for translating advanced technological potential into credible, sustainable combat power.

2. The Strategic Mandate for Scale and Attritable Autonomy

The strategic imperative driving the rapid procurement of unmanned systems is the necessity to counter the numerical advantages held by pacing threats, particularly the People’s Republic of China, in the Indo-Pacific region.³ The 2022 National Defense Strategy identifies the PRC as the Department’s pacing challenge, noting its rapid military modernization and capability to project power across multiple domains.¹² To meet this challenge, the Department of Defense is leveraging domestic private industry to bridge the “valley of death” between prototype development and operational fielding.²

The most prominent manifestation of this shift is the Replicator initiative, managed by the Defense Innovation Unit.¹ Announced in August 2023, the first iteration of the initiative, Replicator 1, focuses on fielding thousands of All-Domain Attritable Autonomous systems across aerial, ground, maritime, and space domains within an aggressive 18-to-24-month timeline.¹ The second phase, Replicator 2, targets counter-small unmanned aerial systems capabilities, reflecting immediate tactical lessons learned from ongoing conflicts in Eastern Europe.¹ The ultimate goal is to field “attritable” capabilities—unmanned platforms built affordably enough that commanders can tolerate a high degree of risk in their employment, utilizing them as expendable assets to penetrate anti-access/area denial networks.¹

However, the speed of this acquisition strategy introduces significant risks regarding long-term sustainment. Transitioning fielded systems to full operational capability requires the military services to make extensive modifications across the DOTmLPF-P framework, which dictates the integration of Doctrine, Organization, Training, materiel, Leadership, Personnel, Facilities, and Policy.² Failure to systematically modify the “Facilities” and “materiel” pillars specifically prevents new technologies from being effectively integrated into the logistics enterprise.² A formation that relies on thousands of autonomous systems requires an industrial-scale pipeline of replacement airframes, proprietary components, and sensitive batteries to sustain continuous operations.²

Historically, the military has struggled when technological vision outpaces logistical reality. During the Cold War, the rapid integration of atomic artillery was driven by a desire to leverage cutting-edge technology to increase standoff distance and theoretically reduce the logistical burden of conventional ammunition.¹⁴ However, this rapid incorporation led to inefficient, impractical systems with massive support requirements that were quickly discontinued.¹⁴ Similarly, the assumption that autonomous systems inherently possess “no maintenance tail” because they lack human crews is a critical miscalculation.¹⁵ When combat operations transition to a model reliant on mass drone swarms, the consumption rate of these platforms mirrors that of traditional artillery.¹⁷ Yet, unlike inert artillery shells, drones are highly complex electronic devices requiring a supply chain optimized for low-density, high-fragility cargo, conflicting directly with traditional military bulk transport mechanisms.

3. The Physical Reality of Airframes: Packaging and Fragility Constraints

The physical footprint of an unmanned aerial system in transit is dictated not merely by the dimensions of the airframe, but by the rigorous packaging standards required to ensure the system survives global military transport. The Department of Defense logistics enterprise subjects cargo to extreme environmental and mechanical stresses, including rapid depressurization, severe temperature fluctuations, and high-impact kinetic shocks during loading and offloading.¹⁹

To mitigate these risks, all items entering the military distribution system must adhere to stringent specifications, notably MIL-STD-2073-1C for preservation methods and ASTM D3951 for commercial packaging.¹⁹ Under these standards, the Defense Logistics Agency mandates that materiel be protected from physical damage, corrosion, and mechanical malfunction.¹⁹ Crucially, standard commercial loose-fill cushioning and dunnage are strictly prohibited for all DoD shipments and aerospace facilities.²² Items classified as fragile, which includes nearly all unmanned aerial systems due to their composite wings, sensitive control surfaces, and precision electro-optical/infrared sensor gimbals, must utilize custom-molded compartmentalization, dense foam wrapping, or robust crating.²⁰

The engineering physics of packaging dictate that adequate protection requires significant volume. The total cushion thickness required to protect a fragile item is calculated as the sum of the deflection requirement for limiting shock, combined with added thickness to prevent the cushion from “bottoming out” under extreme strain.²³ For highly sensitive optics and lightweight composite structures, this necessitates thick layers of specialized foam. Consequently, a standard shipping container packed with military drones consists predominantly of protective air and foam rather than the actual munition.

When platforms like loitering munitions are packaged into specialized multi-application shipping containers or multi-tube launchers, the ratio of protective packaging to actual munition weight becomes severely skewed.²¹ While this packaging is absolutely mandatory to ensure that the systems arrive in operational condition, it vastly expands the physical envelope of the cargo. The defense industrial base optimizes for the performance of the drone in the air, but the logistics enterprise must contend with the volume of the crate on the ground. This disconnect results in massive inefficiencies when calculating cargo loads, as the protective measures required for mass drone shipments consume disproportionate amounts of space inside standard transport vehicles and aircraft.

4. Volumetric Inefficiency and the Tyranny of Cube

The intersection of fragile airframe designs and rigorous military packaging standards yields the single greatest physical barrier to deploying mass unmanned aerial systems: volumetric inefficiency. In the discipline of military logistics, the capacity of any transport asset is defined by two primary metrics: the maximum weight limit (payload) and the maximum volume limit (cube).⁶ Efficient logistics operations strive to balance these two factors, aiming to maximize the available space without exceeding structural weight restrictions.⁶

Due to aerodynamic and propulsion requirements, drone airframes consist largely of empty space. Even when wings and control surfaces are folded, detached, or housed within launch tubes, the volumetric footprint remains disproportionately large relative to the mass of the object.²⁵ In logistics terminology, this creates a severe “cube utilization” paradox.²⁶ When shipping mass quantities of these systems, transport aircraft and ground vehicles “cube out”—meaning they fill all available physical space—while utilizing only a small fraction of their maximum weight capacity.²⁶ This low weight-to-volume ratio fundamentally degrades transportation efficiency, leading to wasted payload capacity and the necessity for additional transport assets to move the same amount of combat power.²⁵

An analysis of the leading systems currently selected for accelerated fielding initiatives clearly illustrates this volumetric challenge. The AeroVironment Switchblade 600, an extended-range loitering munition procured for its precision strike capabilities, represents an all-in-one, tube-launched system.³⁰ The munition itself is relatively light, weighing 15 kilograms (33 pounds).³¹ However, the All-Up Round, which includes the sealed launch tube required for transport and deployment, weighs 29.5 kilograms (65 pounds).³¹ The dimensions of this single launcher are 1.5 meters (60 inches) in length and 19.2 centimeters (7.5 inches) in diameter.³⁰

Similarly, the Anduril Altius-600, designated as a multi-role autonomous air vehicle for intelligence, surveillance, and reconnaissance missions, features a maximum takeoff weight of only 12.25 kilograms (27 pounds).³² Yet, it possesses a length of 1 meter (3.3 feet) and a deployed wingspan of 2.54 meters (8.3 feet).³² Like the Switchblade, it is typically housed in a launch tube for transport, creating a long, awkward cylindrical profile that is difficult to stack efficiently without specialized external racking systems.

When moving multiple thousands of these systems, as directed by current strategic initiatives, the spatial footprint expands exponentially. If a single shipping crate contains ten Switchblade 600 All-Up Rounds, the vast majority of the volume within that crate is dedicated to the void space between the cylindrical tubes and the required protective padding. This low weight-to-volume ratio dictates that the strategic logistics pipeline must focus almost exclusively on managing volume rather than weight, a reality that directly impacts the utility of the United States’ primary means of global power projection: strategic airlift.

5. Strategic Airlift Strains: The Pallet versus Container Dilemma

The United States relies upon strategic airlift to project power globally, depending primarily on the Lockheed C-5M Super Galaxy for outsized, heavy cargo and the Boeing C-17 Globemaster III for flexible, direct-to-theater delivery.³⁵ The C-17 forms the backbone of rapid strategic delivery, capable of operating from relatively short, austere runways in contested environments.³⁶ As the Air Force explores the Next Generation Airlift program to eventually replace both legacy platforms with a single blended-wing-body design by the 2040s, current operational planning must optimize the existing C-17 fleet.³⁵

The C-17 has a maximum allowable cabin load of 172,200 pounds.⁷ However, because mass drone operations represent volumetric burdens rather than weight burdens, the aircraft will rarely approach this maximum allowable cabin load when transporting unmanned assets. The methodology utilized to load the aircraft—specifically the choice between utilizing 463L master pallets or standard International Organization for Standardization (ISO) containers—creates drastic differences in throughput efficiency and sortie generation.

The HCU-6/E or 463L Master Pallet is the standardized platform for military air cargo, utilized extensively across the Department of Defense and the Civil Reserve Air Fleet.³⁸ Each pallet measures 88 inches by 108 inches, providing a usable surface area for cargo stacking, with a maximum allowable height profile of 96 inches for standard C-17 positions.³⁸ The tare, or empty, weight of a single 463L pallet is highly efficient at only 354 pounds.⁷ A C-17 can accommodate up to 18 of these pallets in its standard logistical configuration.⁷

However, when loading fragile drone crates onto 463L pallets, logistics planners are severely constrained. Protective crates cannot be stacked indefinitely without risking structural damage to the lower tiers or exceeding the pounds-per-square-inch limits of the pallet skin.⁴⁰ Due to the awkward dimensions of drone launch tubes and their protective casing, the stacking proficiency on 463L pallets generally yields a maximum cube utilization of only 67 to 68 percent.⁷

To protect sensitive electronics, mitigate the risk of battery fires, and prevent crushing, there is a strong operational preference to ship drones inside rigid 20-foot ISO containers. ISO containers provide environmental sealing, security, and superior internal cube utilization rates—approximately 75 percent—because boxes can be packed tightly against the rigid steel walls.⁷

Yet, the decision to utilize ISO containers exacts a devastating toll on strategic airlift capabilities due to tare weight. A single 20-foot ISO container has a tare weight of approximately 4,770 pounds.⁷ To load these flat-bottomed containers onto the C-17’s internal roller system, they must be mounted on specialized adapter pallets, which add an additional 1,600 pounds. This brings the total empty weight of the containment system to over 6,300 pounds per single unit.⁷

While a C-17 can carry 18 lightweight 463L pallets, the physical dimensions and floor lock configurations of the aircraft mean it can only accommodate a maximum of 6 to 8 ISO containers.⁷ The mathematical outcome of this configuration choice is stark:

• Palletized Configuration: 18 empty pallets possess a combined tare weight of 6,372 pounds.
• Containerized Configuration: 6 ISO containers mounted on adapters possess a combined tare weight of 38,220 pounds.⁷

This indicates that simply choosing to ship fragile drones in standard ISO containers instead of on pallets strips the C-17 of nearly 31,848 pounds of net cargo capacity per sortie before a single drone is loaded.⁷

The downstream effect of cubing out aircraft and suffering high tare weight penalties is a geometric increase in the number of strategic airlift sorties required to move a given number of drones into a theater of operations. If a Combatant Command requires 5,000 loitering munitions rapidly deployed to repel an advance, and the C-17s are flying largely empty by weight but completely full by volume, the logistics pipeline becomes heavily congested.⁷

This reality creates severe operational vulnerabilities. The Air Force’s Agile Combat Employment doctrine relies on moving assets swiftly between hub and spoke locations to complicate adversary targeting.⁴³ However, if strategic airlift is forced to conduct multiple, multi-day operations simply to move high-volume drone crates, it fails to get inside the adversary’s targeting cycle.⁴³ The spoke base becomes highly vulnerable to long-range precision fires and anti-access/area denial networks.³⁷ To mitigate ground time and exposure, mobility forces are actively testing experimental offload techniques, such as “Method C,” which allows aircrews to safely winch palletized cargo off the aft ramp of a C-17 at a low angle without relying on ground-based forklifts.⁴⁴ While innovative, such tactical workarounds do not solve the fundamental volumetric inefficiency of the cargo itself.

6. Hazardous Materials Logistics: The Lithium-Ion Bottleneck

While the fragile airframes dictate the volumetric footprint of the drone swarm, the energy storage mechanisms within the drones dictate the regulatory and safety footprint. The absolute reliance on lithium-ion and lithium-polymer batteries represents the single greatest logistical vulnerability in mass drone operations.

Modern military drones depend on high-density lithium chemistries to satisfy stringent Size, Weight, and Power requirements.⁴⁵ Lithium-ion remains the standard due to its proven balance of energy density and maturity, while lithium-polymer variants are favored for small tactical platforms where maximum discharge rates are required.⁴⁶ However, the exact energy density that provides extended loiter times and sprint speeds makes these batteries highly volatile.⁹ Acute exposure to high ambient temperatures, mechanical damage during transit, or internal cell faults can readily induce thermal runaway.⁹ This cascading chemical reaction releases extreme heat, toxic gases, and self-sustaining fires that cannot be easily extinguished by conventional means.⁹

Because fires can spread rapidly from one cell to the next in a densely packed container, thermal management and regulatory compliance during storage and transport are non-negotiable.⁹ The Department of Defense enforces strict policies regarding the handling, storage, and movement of lithium batteries to mitigate chemical, flammable, and electrical hazards.⁴⁸ The regulations delineate specific limitations based on the power capacity of the cells.

Data derived from DoD policies on lithium battery movement and storage.⁴⁸

While small lithium batteries found in personal electronics fall under these limited quantity thresholds, military drone batteries routinely exceed these limits, placing them into highly regulated hazardous materials categories.⁴⁸ The logistical burden is further compounded by strict supply chain requirements. DoD Manual 4140.01 mandates rigorous quality programs, the use of Automated Information Technology for tracking, and mandatory nonconformance reporting to ensure that compromised or counterfeit cells do not enter the supply system.⁵⁰ Furthermore, recent National Defense Authorization Act compliance guidelines emphasize supply chain transparency and traceable cell manufacturing, requiring battery suppliers to maintain comprehensive provenance documentation.⁴⁷

Perhaps the most disruptive logistical constraint is the current DoD policy that specifically prohibits all types and sizes of lithium batteries from long-term, non-temporary storage in standard, unmodified facilities.⁴⁸ This prohibition forces the logistics enterprise to constantly move batteries rather than stockpile them, conflicting directly with the requirement to build up reserves for major combat operations.

7. Pre-Positioned War Reserve Materiel and Storage Deficiencies

To rapidly respond to regional contingencies without overwhelming the global transportation network, the military relies on Pre-positioned War Reserve Materiel (PWRM).¹² This materiel is strategically located ashore and afloat to facilitate a timely response during the initial phases of an operation, serving as starter stock until sustainable logistical lines of communication can be established.¹²

However, the current WRM framework is structurally deficient for the era of electrified warfare. Historically optimized for bulk petroleum, conventional ammunition, and inert repair parts, the WRM framework currently lacks the dedicated infrastructure for storing high volumes of tactical batteries and Tactical Energy Storage systems.¹² Storing thousands of high-capacity drone batteries in pre-positioned stocks presents unique risks due to varying shelf-lives based on battery chemistry and the necessity for continuous health monitoring.⁸

Storing lithium-ion batteries in standard, non-climate-controlled ISO containers or warehouses exposes them to severe solar loading and extreme ambient temperatures, particularly during the summer months in the Middle East or the Indo-Pacific.⁹ This exposure severely degrades cell health and exponentially increases the risk of spontaneous thermal runaway.⁹ To safely stockpile these assets forward, the military must invest in specialized, climate-controlled chemical storage buildings or heavily modified ISO containers.¹⁰

Industrial solutions, such as DrumLoc buildings, are outfitted with continuous cooling systems designed to maintain internal temperatures below 80°F, ensuring the chemical stability of the lithium cells.¹⁰ Furthermore, these containers must be equipped with multi-layered safety features, including advanced early-warning smoke detection, specialized fire suppression systems tailored specifically for lithium fires, and structural reinforcement to isolate potential blasts from the rest of the supply dump.¹⁰

The integration of these heavy, specialized, power-drawing containers into the logistical flow further compounds the airlift and volumetric challenges discussed previously. Moving a climate-controlled container requires continuous auxiliary power during transit, limiting interoperability with standard civilian logistics vessels and demanding specialized handling by military sealift and airlift commands. The logistics tail required to support the batteries is, in many ways, more complex than the tail required to support the airframes.

8. Forward Operating Base Power Generation Constraints

Assuming the platforms and their associated batteries successfully navigate the airlift and hazardous materials transport hurdles, they present a final, massive logistical hurdle upon arriving at the Forward Operating Base: electrical power generation.

The future battlefield relies heavily on continuous data transmission, sensor processing, and the physical recharging of thousands of drone batteries.¹¹ A common assumption among defense technologists is that the proliferation of autonomous platforms will eliminate the military’s reliance on fossil fuels.¹¹ This is fundamentally flawed. While battery-powered drones do not consume aviation fuel during flight, the energy required to charge them and process their data shifts the logistical demand to massive quantities of diesel fuel required to run tactical generators at the edge of the battlefield.¹¹

Recent analytical modeling estimating the energy requirements for a standard Army Brigade Combat Team (BCT) operating in the year 2040 highlights the staggering scale of this burden.¹¹ Based on future force structure projections that incorporate extensive autonomous systems—spanning unmanned aircraft, unmanned ground vehicles, and persistent ground sensors—the daily data volume generated by a single BCT is projected to reach 53,370 gigabytes.¹¹

To calculate the energy required to process, store, and transmit this data securely within tactical edge environments, analysts utilize a nominal factor of 5 kilowatt-hours per gigabyte of data.¹¹ Therefore, the daily energy requirement simply to manage the data architecture for these autonomous systems is estimated at 266,850 kilowatt-hours.¹¹ If unmanned aircraft and ground vehicles are utilized continuously throughout the day, matching the duty cycle of ground sensors, this demand scales up by nearly 47 percent to 394,200 kilowatt-hours daily.¹¹

Data derived from estimates of BCT 2040 energy requirements.¹¹

Generating 266,850 kilowatt-hours in an austere, contested environment requires monumental physical infrastructure. Relying solely on conventional diesel power, a BCT would need an array of generators producing 12 megawatts of continuous power, consuming approximately 55,000 liters of diesel fuel every single day.¹¹

This creates a massive logistical tether. Transporting 55,000 liters of fuel daily across contested logistics routes requires continuous convoys of unarmored fuel tankers, which are highly vulnerable to enemy interdiction and long-range fires.¹² Historically, the logistical burden of moving liquid fuel has been a primary limiting factor in operational reach; during conflicts in Afghanistan, it was estimated that moving one gallon of fuel to an austere forward location could consume up to seven gallons of fuel in transit.¹² Therefore, the deployment of thousands of drones does not severe the logistics tether; it merely replaces the ammunition truck with the diesel tanker.

9. Tactical Energy Storage (TES) and Microgrid Architectures

To alleviate the unsustainable strain on generator arrays and fuel convoys, the Department of Defense is heavily investing in Tactical Energy Storage and intelligent microgrid technologies.¹² Programs such as the Defense Innovation Unit’s STEEP (Stable Tactical Expeditionary Electric Power) initiative focus on developing modular, vehicle-transportable microgrids with embedded energy storage and automated power management.⁵⁴

The primary objective is to couple advanced Battery Energy Storage Systems with the military’s existing fleet of Advanced Medium Mobile Power Source (AMMPS) generators.¹² These hybrid architectures provide critical operational flexibility. The BESS absorbs excess power during low-demand periods and discharges it rapidly during peak drone-charging cycles. This concept, known as peak load shaving, ensures that the diesel generators operate at or near their optimum efficiency curves, significantly reducing generator operating hours and overall fuel consumption.¹² Furthermore, the stored energy allows the generators to be shut down entirely, enabling silent watch operations that drastically reduce the acoustic and thermal signatures of the forward operating base.¹²

At the specific level of drone battery management, the proliferation of varied, proprietary charging equipment creates a secondary logistical bottleneck.⁵⁶ Forward bases cannot support hundreds of incompatible charging units. Instead, logistics planners are transitioning toward universal smart battery chargers and containerized charging stations.⁵⁷ These rack-mounted stations utilize sophisticated load-balancing algorithms to prioritize battery charging based on mission urgency, ensuring the local microgrid is not overloaded while preparing mass swarms for simultaneous launch.⁵⁷ For persistent surveillance missions, fully autonomous drone-in-a-box systems integrate the charging station, landing guidance, and power management into a closed-loop system, further reducing the requirement for human intervention.⁵⁷

10. Deployable Facilities, Maintenance, and Human Factors

The physical footprint of mass drone operations extends beyond the storage of hardware and the generation of power; it encompasses the physical facilities required to conduct maintenance and the personnel required to manage the fleet. While the term “attritable” implies expendability in combat, standard peacetime training, pre-deployment preparations, and staging demand that these systems are kept in working order, requiring a dedicated maintenance and support infrastructure.

Operating thousands of platforms requires substantial ground support. Unlike legacy crewed aircraft that rely on established, permanent depot-level repair facilities, mass drone units must conduct frequent assembly, disassembly, software updates, and firmware synchronization at the tactical edge.¹³ To support this maintenance tail in austere environments, units rely on highly specialized deployable structures. The Modular Large Area Maintenance Shelter (MLAMS) provides a massive, relocatable fabric structure capable of housing drone assembly and repair operations.⁵⁹ An 83-foot by 142-foot LAMS, designed specifically for UAV maintenance, provides over 11,000 square feet of environmentally protected workspace.⁶⁰ However, erecting this facility requires shipping the components in both a 20-foot and 40-foot ISO container and demands hundreds of man-hours and heavy lifting equipment to assemble.⁶⁰

For smaller, more rapid deployments, tactical logistics shelters built into standard 20-foot ISO containers are utilized.⁶¹ These shelters can be transported via C-17 or C-130 and provide climate-controlled, secure environments for sensitive electronics diagnostics, battery health monitoring, and post-mission data analysis.⁶¹ Yet, as established, the weight penalty of relying on heavy ISO containers for base infrastructure severely limits the speed at which these capabilities can be airlifted into a contested theater.

Furthermore, human factors research indicates that UAS maintenance personnel face unique challenges compared to traditional aviation mechanics.⁶⁴ Maintainers must manage the reliability of a complex “system of systems,” comprising not just the air vehicle, but the ground control stations, encrypted communication relays, and the battery management infrastructure.⁵⁸ The rapid evolution of technology and the frequent introduction of new airframes via accelerated acquisition programs exacerbate the training burden on these technicians, leading to a lack of historical failure data to guide preventative maintenance.⁵⁸ While some commercial package delivery operations have demonstrated a single pilot controlling up to 24 drones, the ratio of required maintenance personnel to airframes in high-tempo, austere military environments remains a critical operational constraint.⁶⁴

11. Project Convergence and the Shift to Predictive Logistics

To manage the immense logistical complexity of sustaining mass drone fleets across vast distances, the Department of Defense is aggressively pursuing predictive logistics capabilities. These concepts have been tested extensively during the Army’s Project Convergence exercises, specifically Capstone 5 (PC-C5) held at the National Training Center.⁶⁶

The current logistics paradigm relies heavily on reactive resupply—ordering a replacement drone, component, or battery only after a failure occurs or inventory is depleted.⁶⁶ In a contested logistics environment, where adversary forces actively target supply lines and strategic airlift is constrained by volumetric inefficiencies, reactive sustainment results in operational culmination.

Predictive logistics seeks to invert this model by utilizing artificial intelligence, machine learning, and a unified digital backbone known as Next Generation Command and Control (NGC2).⁶⁶ By continuously analyzing telemetry data from deployed drone swarms, battery degradation metrics from smart chargers, and historical consumption rates, predictive algorithms can forecast supply shortages before they impact the mission.⁶⁶ This capability provides commanders with a common operating picture that is timely and actionable, allowing logisticians to stage the necessary replacement airframes, batteries, and repair components at the correct forward operating base in anticipation of demand.⁶⁶ Optimizing the flow of heavy pallets and ISO containers through the contested aerial port network based on AI-driven forecasts is essential to maintaining momentum during large-scale combat operations.

12. Strategic Imperatives for DoD Leadership

The successful execution of strategic initiatives designed to field thousands of autonomous systems rests fundamentally upon the Department of Defense’s ability to overhaul its approach to physical logistics. Viewing the drone solely as a technological marvel, while ignoring the physics of transporting, storing, and powering it, guarantees operational paralysis in a major conflict. To ensure these platforms can reliably reach and operate within contested theaters, leadership must prioritize the following systemic imperatives:

1. Mandate Volumetric Efficiency in Acquisition Criteria The defense acquisition process for unmanned systems must be restructured to heavily weight “logistics footprint” and “cube utilization” as primary evaluation criteria, equal in importance to flight performance and lethality.⁶⁹ Programs must financially incentivize vendors to design systems with folding, collapsible, or modular architectures that pack densely onto standard 463L pallets. A platform that possesses superior flight characteristics but requires a volumetric footprint that cripples strategic airlift is a net-negative to the Combatant Commander. Furthermore, packaging standards must transition from bulky commercial foam to high-density, stackable, military-grade transit cases that balance delicate shock protection with spatial efficiency.

2. Institutionalize Tactical Energy Storage in War Reserves The current paradigm of Pre-positioned War Reserve Materiel is obsolete for the demands of electrified warfare. The Defense Logistics Agency and the Military Departments must rapidly procure and integrate high-capacity batteries and mobile Tactical Energy Storage systems into pre-positioned stocks globally.¹² These energy assets must be managed with the same rigorous shelf-life monitoring and climate-control standards currently applied to sensitive munitions and pharmaceuticals.¹²

3. Procure Specialized Hazardous Materials Transport Infrastructure The military must rapidly scale its inventory of climate-controlled, structurally reinforced ISO containers designed specifically for the transport and forward storage of Class 9 lithium batteries.⁹ Relying on general-purpose warehousing or standard shipping containers exposes the fleet to catastrophic thermal runaway events, particularly in the extreme temperatures of the Pacific or Middle Eastern theaters. The acquisition of these containers must be paired with dedicated auxiliary power units to ensure continuous cooling during transit across the global supply chain.

4. Align Force Structure with Power Generation Realities Commanders and force planners must explicitly account for the massive electrical tether associated with mass drone operations. Operational planning must transition away from the false assumption that autonomous drones eliminate fuel requirements; their extensive use directly dictates the requirement for tens of thousands of liters of diesel fuel daily to power tactical generators at the edge.¹¹ Aggressive investments in microgrid automation, solar augmentation, and advanced load-balancing Battery Energy Storage Systems are critical to reducing this daily fuel demand and preserving operational reach.¹¹

The era of mass autonomous warfare will not be won solely by the sophistication of the artificial intelligence algorithms or the aerodynamic speed of the airframes. It will be decided by the industrial and logistical capacity to physically move lightweight, high-volume, highly volatile systems across oceans, sustain their massive power requirements in austere environments, and manage their complex maintenance tails at the tactical edge.

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Sources Used

1. Deep Dive: Pentagon’s Replicator Initiative Raises Questions | Inkstick, accessed April 24, 2026, https://inkstickmedia.com/deep-dive-pentagons-replicator-initiative-raises-questions/
2. Is Replicator Replicable? | The Belfer Center for Science and …, accessed April 24, 2026, https://www.belfercenter.org/research-analysis/replicator-replicable
3. DOD Innovation Official Discusses Progress on Replicator – Department of War, accessed April 24, 2026, https://www.war.gov/News/News-Stories/Article/Article/3999474/dod-innovation-official-discusses-progress-on-replicator/
4. Hicks Discusses Replicator Initiative > Department of Defense Manufacturing Technology Program > News Display – DoD ManTech, accessed April 24, 2026, https://www.dodmantech.mil/News/News-Display/Article/3518827/hicks-discusses-replicator-initiative/
5. M W J – Modern War Institute -, accessed April 24, 2026, https://mwi.westpoint.edu/wp-content/uploads/2026/03/Modern-War-Journal-MWJ-second-edition-final-draft-as-of-12MAR26-pdf-1.pdf
6. Effects of Alternative Performance Criteria upon Composition of Air Transportable Spare Parts Kits – AFIT Scholar, accessed April 24, 2026, https://scholar.afit.edu/cgi/viewcontent.cgi?article=5589&context=etd
7. C-17 Container Study. – DTIC, accessed April 24, 2026, https://apps.dtic.mil/sti/tr/pdf/ADA362578.pdf
8. Drone Battery Storage & Safety: The Essential Guide, accessed April 24, 2026, https://terra-drone.com.sa/drone-battery-storage-safety-the-essential-guide/
9. “Lithium-Ion Batteries Hazard and Use Assessment Final Report.” – Nuclear Regulatory Commission, accessed April 24, 2026, https://www.nrc.gov/docs/ml1719/ml17191a294.pdf
10. Lithium Ion Battery Storage Requirements, accessed April 24, 2026, https://www.uschemicalstorage.com/lithium-ion-battery-storage-requirements/
11. The Energy Requirements for Processing Data on the Future …, accessed April 24, 2026, https://www.armyupress.army.mil/Journals/Military-Review/English-Edition-Archives/January-February-2026/Energy-Requirements/
12. Incorporating Tactical Energy Storage into War Reserves: DLA’s …, accessed April 24, 2026, https://www.dla.mil/About-DLA/News/News-Article-View/Article/4347210/incorporating-tactical-energy-storage-into-war-reserves-dlas-vital-role-in-sust/
13. Security & Defence European, accessed April 24, 2026, https://euro-sd.com/wp-content/uploads/2021/04/ESD_02_2021_WEB.pdf
14. Lessons Learned and Unlearned: The Drivers of US Indirect-Fire Innovation Brennan S. Deveraux, Major, US – Army University Press, accessed April 24, 2026, https://www.armyupress.army.mil/Portals/7/Research%20and%20Books/2024/Feb/Deveraux-Lessons-Learned-2024.pdf
15. The J ournal of the Unite d S e rvice Institution of India OC T OBER -DEC EMBER 2025 US I, accessed April 24, 2026, https://usiofindia.org/pdf/USI_Journal_%20Oct_Dec_2025_Final.pdf
16. Imagining the Drone Air Force – Austin Vernon’s Blog, accessed April 24, 2026, https://www.austinvernon.site/blog/droneairforce.html
17. Smart Munitions Market Outlook 2026-2034 – Intel Market Research, accessed April 24, 2026, https://www.intelmarketresearch.com/smart-munitions-2025-2032-582-1916
18. AY 2024-2025 A New Arsenal for A New Era: Balancing Affordable Mass with Exquisite Capabilities WEAPONS INDUSTRY STUDY – Eisenhower School, accessed April 24, 2026, https://es.ndu.edu/Portals/75/Documents/Industry%20Study%20Reports/reports/2025/AY25%20Weapons-Cleared.pdf?ver=nyw0s8HSF-gRcQQaCOA7Pg%3D%3D
19. Vendor Preservation, Packaging, Packing, and Marking Process – DLA, accessed April 24, 2026, https://www.dla.mil/Logistics-Operations/Packaging/Vendor-Preservation-Packaging-Packing-and-Marking-Process/
20. Crating and Packaging Military Assets: A Basic Guide, accessed April 24, 2026, https://www.connerpackaging.com/crating-and-packaging-military-assets/
21. Department of Defense: Standard Practice for Military Packaging. – DTIC, accessed April 24, 2026, https://apps.dtic.mil/sti/tr/pdf/ADA327827.pdf
22. DLA Packaging, accessed April 24, 2026, https://www.dla.mil/Logistics-Operations/Packaging/
23. Features of Effective Packaging and Transport for Artwork – Technical Bulletin 34, accessed April 24, 2026, https://www.canada.ca/en/conservation-institute/services/conservation-preservation-publications/technical-bulletins/effective-packaging-transport-artwork.html
24. NAVAL POSTGRADUATE SCHOOL – DTIC, accessed April 24, 2026, https://apps.dtic.mil/sti/pdfs/AD1184798.pdf
25. FOOD PACKAGING TECHNOLOGY | Polymer Innovation Blog, accessed April 24, 2026, https://polymerinnovationblog.com/wp-content/uploads/2017/02/Food-Packaging-Technology.pdf
26. freight glossary terms and logistics management words, accessed April 24, 2026, https://dcm.com.eg/glossary/
27. Environmental, Operational and Financial Sustainability of Packaging Methods in Delivery Businesses – DSpace@MIT, accessed April 24, 2026, https://dspace.mit.edu/bitstream/handle/1721.1/61184/700932931-MIT.pdf?sequence=2&isAllowed=y
28. Delivery process-review and improvement proposals – Theseus, accessed April 24, 2026, https://www.theseus.fi/bitstream/handle/10024/111731/Thesis%202016-theseus%20version.pdf?sequence=1
29. Ultimate Guide to FTL and LTL Route Optimization – CR Express, accessed April 24, 2026, https://www.crexpressinc.com/blog/ai/ultimate-guide-ftl-ltl-route-optimization
30. Switchblade® 600 represents the next generation of extended-range loitering munitions. Featuring high precision optics and ove – AeroVironment, Inc., accessed April 24, 2026, https://www.avinc.com/images/uploads/product_docs/Switchblade600_Datasheet.pdf
31. Switchblade® 600 – AeroVironment, accessed April 24, 2026, https://www.avinc.com/solution/switchblade-600/
32. Anduril ALTIUS – Designation-Systems.Net, accessed April 24, 2026, https://www.designation-systems.net/dusrm/app4/altius.html
33. ALTIUS-600 Small Unmanned Aircraft System, USA – Air Force Technology, accessed April 24, 2026, https://www.airforce-technology.com/projects/altius-600-small-unmanned-aircraft-system/
34. ALTIUS-600 Drone – Full Specifications | TheDefenseWatch.com, accessed April 24, 2026, https://thedefensewatch.com/product/altius-600-drone/
35. Why The US Air Force Believes 1 Aircraft Can Replace Both The C-17 Globemaster & C-5 Galaxy – Simple Flying, accessed April 24, 2026, https://simpleflying.com/us-air-force-aircraft-replace-both-c-17-globemaster-c-5-galaxy/
36. U.S. Air Force Mobility Aircraft 101 – CSIS Aerospace Security, accessed April 24, 2026, https://aerospace.csis.org/aerospace101/u-s-air-force-mobility-aircraft/
37. AMC Boss: One Airplane to Replace C-17 and C-5 Transports, accessed April 24, 2026, https://www.airandspaceforces.com/air-mobility-command-c-17-replace/
38. 463L master pallet – Wikipedia, accessed April 24, 2026, https://en.wikipedia.org/wiki/463L_master_pallet
39. Palletized Systems Cargo Pallets – AAR Corp., accessed April 24, 2026, https://www.aarcorp.com/globalassets/government-solutions/mobility-systems/aar_cargo-pallets-final_2023.pdf
40. 463l pallet and dunnage system evaluation – ROSA P, accessed April 24, 2026, https://rosap.ntl.bts.gov/view/dot/49622/dot_49622_DS1.pdf
41. Aircraft Load Planning and Documentation, Part III, Appendix V – USTransCOM, accessed April 24, 2026, https://www.ustranscom.mil/dtr/part-iii/dtr_part_iii_app_v.pdf
42. System 463L Pallets and Nets, Part VI, Chapter 608 – USTransCOM, accessed April 24, 2026, https://www.ustranscom.mil/dtr/part-vi/dtr_part_vi_609.pdf
43. Air and Space Operations Review – Air University, accessed April 24, 2026, https://www.airuniversity.af.edu/Portals/10/ASOR/Journals/Volume-4_Number-2/ASOR_Volume_4_Number_2.pdf
44. 3rd AS drives testing of new C-17 combat offload method – DVIDS, accessed April 24, 2026, https://www.dvidshub.net/news/463014/3rd-drives-testing-new-c-17-combat-offload-method
45. Drone Battery Packs – UAV, UGV & ROV Power Packs – Unmanned Systems Technology, accessed April 24, 2026, https://www.unmannedsystemstechnology.com/expo/battery-packs/
46. Military Drone Battery Suppliers & Manufacturers – Defense Advancement, accessed April 24, 2026, https://www.defenseadvancement.com/suppliers/military-drone-batteries/
47. NDAA-Compliant Batteries for Drones & UAS – Unmanned Systems Technology, accessed April 24, 2026, https://www.unmannedsystemstechnology.com/expo/ndaa-compliant-batteries/
48. New DOD policy limiting storage, movement of certain lithium …, accessed April 24, 2026, https://www.army.mil/article/266542/new_dod_policy_limiting_storage_movement_of_certain_lithium_batteries_takes_effect_on_monday
49. “It’s Your Move” Department of Defense (DOD) Civilian Employees, Part IV A, Attachment A-K2 – USTransCOM, accessed April 24, 2026, https://www.ustranscom.mil/dtr/part-iv/dtr_part_iv_att_A-k_2.pdf
50. DoD Manual 4140.01, Volume 3, “DoD Supply Chain Materiel Management Procedures – Executive Services Directorate, accessed April 24, 2026, https://www.esd.whs.mil/Portals/54/Documents/DD/issuances/dodm/414001_vol3.PDF?ver=6FxZP1zDmqytGggDjsGFVw%3D%3D
51. DoD Manual 4140.01, Volume 7, February 10, 2014, accessed April 24, 2026, https://www.hsdl.org/c/view?docid=749848
52. DoDI 4140.01, “DoD Supply Chain Materiel Management Policy,” March 6, 2019 – Executive Services Directorate, accessed April 24, 2026, https://www.esd.whs.mil/Portals/54/Documents/DD/issuances/dodi/414001p.pdf
53. Battery Storage Risks: How to Securely Store BESS Units Pre-Installation, accessed April 24, 2026, https://johnsoncommercialsolutions.com/battery-storage-boom-how-to-securely-store-bess-units-pre-installation/
54. Enhanced Energy Storage, Intelligent Power Management Systems …, accessed April 24, 2026, https://www.diu.mil/latest/enhanced-energy-storage-and-intelligent-power-management-systems-for-defense
55. Battery Energy Storage Systems in Defense | White Paper – POWR2, accessed April 24, 2026, https://powr2.com/white-paper-powering-mission-readiness/
56. The challenges of powering military drones – Galvion, accessed April 24, 2026, https://www.galvion.com/case-study/challenges-of-powering-drones
57. Battery Chargers for Drones & Robotics – Unmanned Systems Technology, accessed April 24, 2026, https://www.unmannedsystemstechnology.com/expo/battery-chargers/
58. Human Challenges in the Maintenance of Unmanned Aircraft Systems, accessed April 24, 2026, https://human-factors.arc.nasa.gov/publications/UAV_interimreport_Hobbs_Herwitz.pdf
59. Large Area Maintenance Shelters (LAMS), accessed April 24, 2026, https://celinamilitaryshelters.com/lams/
60. appendix a, shelter product data sheet, revision a – DLA, accessed April 24, 2026, https://www.dla.mil/Portals/104/Documents/TroopSupport/CloTex/shelters/Celina/C23083X142TG-G.pdf
61. Standard ISO 20 ft Shelter – Tect, accessed April 24, 2026, https://www.tect.co.il/wp-content/uploads/2021/02/ISO-MIL-SHELTER-ascentech.pdf
62. Tactical & Logistics Shelter Systems – Varley Group, accessed April 24, 2026, https://varleygroup.com/defence/land/tactical-logistics-shelter-systems/
63. ISO 20 ft – Milshel, accessed April 24, 2026, https://www.milshel.net/iso-shelter/iso-20-ft/
64. UAS Air Carrier Operations Survey: Crew and Staffing Requirements – Federal Aviation Administration, accessed April 24, 2026, https://www.faa.gov/sites/faa.gov/files/UAS%20Air%20Carrier%20Operations%20Survey-Crew%20and%20Staffing%20Requirements.pdf
65. Considerations for Unmanned Aircraft Systems Maintenance and Reliability, accessed April 24, 2026, https://micronanoeducation.org/journal/volume-1-issue-1/considerations-for-unmanned-aircraft-systems-maintenance-and-reliability/
66. NGC2 at the Tactical Edge: Enabling Predictive Logistics for Decision Dominance | Article, accessed April 24, 2026, https://www.army.mil/article/290032/ngc2_at_the_tactical_edge_enabling_predictive_logistics_for_decision_dominance
67. Project Convergence Capstone 5 experiments at NTC | Article | The United States Army, accessed April 24, 2026, https://www.army.mil/article/284397/project_convergence_capstone_5_experiments_at_ntc
68. Project Convergence | U.S. Department of War, accessed April 24, 2026, https://www.war.gov/Spotlights/Project-Convergence/
69. From “Plan and Pray” to “Sense and Respond” – International Cost …, accessed April 24, 2026, https://www.iceaaonline.com/wp-content/uploads/2024/06/STY01-Wekluk-Wargaming-Defense-Acquisition-Paper.pdf
70. SERVICEMEMBER QUALITY OF LIFE IMPROVEMENT AND NATIONAL DEFENSE AUTHORIZATION ACT FOR FISCAL YEAR 2025 R E P O R T COMMITTEE ON A, accessed April 24, 2026, https://www.nationalguard.mil/Portals/31/Documents/PersonalStaff/LegislativeLiaison/FY25/FY25%20NDAA%20Report%20(H.R.%208070).pdf
71. DoD Manual 4140.01, Volume 5, “DoD Supply Chain Materiel Management Procedures – Executive Services Directorate, accessed April 24, 2026, https://www.esd.whs.mil/Portals/54/Documents/DD/issuances/414001m/414001v5.PDF?ver=-X4KmyoVoWHNUf5PYULJjA%3D%3D

1. Executive Summary

The United States Department of Defense (DoD) is undertaking a structural pivot in its force posture, moving toward the integration of autonomous and uncrewed systems (UxS) at a transformative scale. Fiscal planning reflects this transition, with extensive capital allocated toward reshaping the battlefield. Recent budget requests demonstrate a prioritization of drone warfare and counter-drone technologies, projecting tens of billions of dollars toward autonomy, platform acquisition, contested logistics, and munitions over the coming fiscal years.¹ Central to this transition is the Replicator initiative, a framework designed to overcome traditional bureaucratic inertia and field multiple thousands of all-domain, attritable autonomous (ADA2) systems within an aggressive timeframe to counter peer adversary mass.³

However, a critical strategic vulnerability exists within this paradigm shift: the procurement and manufacturing of uncrewed airframes are vastly outpacing the industrial capacity to arm them. The defense apparatus exhibits a tendency to focus heavily on the aerial platforms themselves—prioritizing software, autonomy, and flight characteristics—while systematically underestimating the industrial base required to mass-produce miniaturized precision micro-munitions, modular warheads, and the highly specialized precursor materials they require.⁷ A drone without a reliably sourced, mass-producible munition is relegated to an intelligence, surveillance, and reconnaissance (ISR) role. While ISR remains vital, the strategic intent of modern initiatives is to deliver long-range, distributed kinetic effects.³

This report provides DoD leadership with an objective strategic analysis of the drone-specific munitions and payload supply chain. It moves beyond the visible tier-one prime contractors to detail the fragile, sub-tier dependencies in critical materials, energetics, and propulsion systems.⁸ Furthermore, it examines the imperative of modular open systems architectures to break vendor lock and scale payload production alongside commercial platform scaling.¹⁰ Finally, it addresses the severe logistical complexities of rearming these autonomous fleets within the context of Distributed Maritime Operations (DMO) and Expeditionary Advanced Base Operations (EABO).¹² In these operational models, the traditional concentration of explosive material in hub-and-spoke supply depots is both tactically hazardous and logistically unfeasible.¹⁵ To successfully enable warfighters with necessary kinetic effects, leadership must recognize that scaling the drone fleet is strategically ineffective without simultaneously scaling the specialized industrial base and logistical networks that manufacture and deliver their lethal payloads.

2. The Platform-Munition Acquisition Imbalance

The modern operational environment demonstrates that mass and attrition have returned as defining characteristics of conventional conflict. Observation of recent high-intensity conflicts reveals staggering consumption rates of both loitering munitions and precision-guided weapons.¹⁷ In these environments, the daily expenditure of precision assets routinely exceeds the monthly or even annual production capacities of Western industrial bases.¹⁷

The DoD has recognized this reality, initiating programs designed to inject mass into the Joint Force. The Replicator initiative aims to field thousands of autonomous systems to offset adversary advantages in mass and geographic positioning.³ Tranche 1 and Tranche 1.2 of the Replicator initiative specifically target the accelerated fielding of loitering munitions, such as the Switchblade-600 and the Altius-600, alongside company-level small uncrewed aerial systems (sUAS) like the Anduril Industries Ghost-X and Performance Drone Works C-100, which are capable of carrying modular payloads.³

Yet, a fundamental imbalance persists in the acquisition ecosystem. The industrial barriers to producing a basic autonomous airframe or quadcopter are relatively low, often leveraging commercial off-the-shelf (COTS) components and civilian manufacturing processes. Conversely, the barriers to producing the kinetic payloads—the warheads, the precision seekers, and the fusing mechanisms—are exceptionally high. The U.S. defense industrial base (DIB) for uncrewed systems is currently categorized as highly fragile, suffering from limited competition, demand uncertainty, and a critical reliance on foreign sources for core components.⁹

2.1. Budgetary Allocations and Priorities

An analysis of the DoD’s Fiscal Year (FY) 2025 budget request highlights the scale of investment in systems and munitions. The request totals $310.7 billion for procurement and research, development, test, and evaluation (RDT&E).¹ While munitions and missiles receive substantial funding, the underlying industrial capacity to absorb these funds and output physical units remains constrained.

Data Source: DoD Comptroller, FY2025 Weapons Investment Report.¹

Furthermore, defense officials have indicated that proposed future budgets, extending into FY 2027, will allocate over $70 billion specifically for military drones and counter-drone weapon systems, representing the largest investment in drone warfare in U.S. history.² Within this long-term planning, approximately $53.6 billion is slated for autonomy, platforms, and contested logistics, while $21 billion is earmarked for munitions and counter-drone technologies.² This financial commitment requires a commensurate expansion of the physical industrial base to produce the required hardware.

2.2. The Fragility of the Uncrewed Systems DIB

A systematic evaluation by the RAND Corporation indicates that the U.S. uncrewed systems industrial base is fundamentally “more fragile than it is critical”.⁹ This terminology suggests that the primary risk lies in the potential loss of existing capabilities rather than the difficulty of replacing them once lost. Factors contributing to this fragility include demand uncertainty, which discourages long-term capital investment by private firms; market concentration, wherein a very limited number of firms are capable of building systems at scale; and significant reliance on foreign sources for selected critical components.⁹

While large prime contractors manage visible risks efficiently, fragility accumulates invisibly at the lower tiers. Small, capital-constrained firms responsible for specific components face single-source dependencies and limited surge capacity.⁸ When demand signals are chaotic and unpredictable, these sub-tier suppliers cannot afford to retain the latent production capacity required to scale up in an emergency.¹⁷

2.3. Historical Context: The Arsenal of Democracy vs. The Knowledge Economy

To contextualize the current industrial shortfall, it is necessary to examine historical defense mobilization. During World War II, the “Arsenal of Democracy” successfully produced nearly 300,000 aircraft and 86,000 tanks.²⁰ This feat was achievable because the U.S. economy was heavily rooted in manufacturing, and latent production capacity existed across civilian sectors that could be rapidly retooled for defense.²⁰ The War Production Board provided a unified, coherent demand signal that eliminated market risk for private companies, guaranteeing material allocations and contracts.¹⁷

By contrast, the contemporary U.S. economy is primarily knowledge-based.²⁰ Decades of policy choices prioritizing peacetime efficiency and just-in-time logistics have eroded the domestic manufacturing base.¹⁷ The defense industrial base is deeply entangled with global supply chains, often relying on adversary-controlled markets for raw materials.⁷ To field the payloads required for modern drone fleets, the DoD cannot rely on latent civilian capacity; it must deliberately construct and secure a dedicated, modernized supply chain.

3. Structural Vulnerabilities in Sub-Tier Material Supply Chains

A modern military drone and its associated kinetic payload rely fundamentally on complex metallurgy and advanced chemistry. The global supply chain for these raw materials is heavily entangled with markets managed by peer competitors, translating supply chain competition into a geopolitical battle for the raw inputs required to employ drones at mass scale.⁷

3.1. Sensors and Seekers: The Precision Bottleneck

The efficacy of a precision micro-munition relies entirely on its ability to autonomously or semi-autonomously locate, fix, and track targets. This requires advanced sensors and seekers, which are bound by distinct material chokepoints.⁷

• Infrared Detectors: High-fidelity thermal seekers are critical for terminal guidance and targeting in contested environments where GPS or visual spectrums are degraded. These seekers rely heavily on highly specialized materials, namely indium antimonide and mercury cadmium telluride.⁷
• Datalinks and Amplifiers: The communication architectures that allow drone swarms to coordinate, or human operators to authorize strikes via “human-in-the-loop” systems, require immense bandwidth and power efficiency. Gallium-Nitride (GaN) power amplifiers are foundational to these datalinks, enabling remote operation and sensor feedback.⁷
• Semiconductor Fabrication: The flight controllers, mission computers, and navigation systems depend on specialized semiconductors. The fabrication facilities for these specific defense-grade chips are complex and limited in number. They require years of capital investment to expand, meaning they cannot organically surge production to meet sudden wartime demands or absorb the shock of global export controls.⁷

3.2. Propulsion Dependencies

Whether for the carrier platform or a specific loitering munition, propulsion relies on materials that are acutely vulnerable to geopolitical weaponization.

• Rare-Earth Magnets: The electric motors providing lift and torque for most sUAS and loitering munitions rely on neodymium-iron-boron (NdFeB) magnets.⁷ Currently, approximately 90% of the global output for these magnets is concentrated in China. Even when the raw materials are mined in allied nations, the complex magnetization and finishing processes remain largely under foreign control, exposing the U.S. to severe disruption.⁷
• Mini-Jet Engines: For longer-range, deep-strike drones and high-speed loitering munitions, electric motors are insufficient, necessitating miniaturized turbojet engines. Currently, there is a massive production bottleneck in Europe and North America for these mini-jet engines.²² These are technically demanding systems built with lightweight alloys and advanced manufacturing methods, including 3D-printed components. Because they were not produced at scale prior to recent global conflicts, European and allied manufacturers—such as Czech-based PBS Group—are stretched to their limits trying to fulfill demand.²³ This creates a structural supply-chain deficit that strictly limits the total number of missile drones that can be fielded.²²

3.3. Structural Materials for Payloads

To maximize the lethality of a micro-munition, the weight of the delivery vehicle must be absolutely minimized. This requires aerospace-grade carbon fiber for the skeletal foundation and specialized alloys, such as aluminum-lithium, to ensure structural integrity while preserving weight margins for the explosive payload.⁷ The global production capacity for these specific alloys and composites is limited and cannot be rapidly scaled in a crisis.

4. The Energetics and Advanced Manufacturing Crisis

While sensors guide the weapon and airframes carry it, energetics provide the actual kinetic effect. The capacity to produce the explosive compounds and propellants required for micro-munitions is arguably the most severe constraint facing the U.S. defense industrial base. The production of drone-specific munitions introduces unique vulnerabilities related to precursor chemicals and weight-optimization requirements.⁷ To maximize lethality on a small platform, energetics must yield high energy output from minimal mass, necessitating advanced chemical formulations.

4.1. The Antiquated Energetics Infrastructure

The U.S. military heavily relies on Government-Owned, Contractor-Operated (GOCO) Army Ammunition Plants (AAPs) to produce energetics, small-caliber ammunition, and high-explosive artillery.²⁵ These facilities have served as the backbone of the arsenal since World War II. Consequently, much of the foundational technology and process infrastructure remains antiquated. For example, the domestic production of RDX and HMX—two of the primary energetic chemicals relied upon by the U.S. military since the 1940s—still utilizes the WWII-era Bachmann process at facilities like the Holston Army Ammunition Plant.²⁶

Relying on 80-year-old manufacturing processes severely limits production throughput and creates single points of failure. The loss of access to even a single precursor chemical could halt the production of an entire class of drones and their payloads. Furthermore, the Department of Defense currently lacks comprehensive visibility below the tier-one contractor level to identify these specific precursor risks.⁷

The National Energetics Plan details the actions required to maintain technical superiority, highlighting systemic challenges.²⁷ Among these are insufficient coordination between science and technology (S&T) and acquisition communities, which stifles the transition of advanced energetics to operational use. Additionally, antiquated Test and Evaluation (T&E) standards fail to accurately characterize the effects of advanced energetic materials designed for extended range and lethality.²⁷

4.2. Modernization Initiatives and the Munitions Campus Model

Recognizing this critical shortfall, the Army has initiated a 15-year Organic Industrial Base (OIB) Modernization Plan, representing an investment of approximately $18 billion to modernize facilities, infrastructure, and retool processes across its 23 arsenals, depots, and ammunition plants.²⁸ As part of this effort, the Joint Program Executive Office for Armaments and Ammunition (JPEO A&A) is leveraging digital engineering and Model-Based Systems Engineering (SysML) to identify process bottlenecks and optimize throughput at these legacy facilities.²⁵

Furthermore, the DoD is exploring public-private partnerships to bypass the limitations of legacy infrastructure. A prime example is the recent groundbreaking of the Munitions Campus in Bloomfield, Indiana.³¹ Supported by a $75 million award from Defense Production Act Title III funding, this campus introduces a shared-infrastructure model that collocates manufacturers of major components, subcomponents, and energetics—such as solid rocket motors (SRMs)—to streamline the supply chain. Prometheus Energetics LLC serves as the anchor tenant for this 1,100-acre development. By clustering industrial capacity in close proximity to the Crane Army Ammunition Activity and Naval Surface Warfare Center Crane, the DoD aims to enable faster, more cost-effective scaling of munitions output across various weapon systems.³¹

4.3. The Workforce Deficit in Advanced Manufacturing

Capital investment in infrastructure cannot yield results without a highly skilled workforce. The production of uncrewed systems and their payloads suffers from critical labor shortages in specialized trades. Assessments of the defense-oriented advanced manufacturing landscape reveal profound deficits in skills related to welding, forging, metal casting, and advanced electronics soldering.⁹

Initiatives such as the Advanced Manufacturing Training Program in Massachusetts and DoD Manufacturing Technology (ManTech) engagements with the Advanced Robotics for Manufacturing (ARM) Institute are attempting to close these gaps through targeted workforce development grants and gap analyses.³² However, training a workforce capable of executing modern, tight-tolerance manufacturing for micro-munitions operates on a multi-year horizon, compounding the immediate challenge of scaling production for rapid fielding initiatives.

5. Overcoming Vendor Lock: Payload Modularity and Open Architecture

To scale payload availability rapidly, the DoD must decouple the development of the drone airframe from the development of the munition. Historically, uncrewed systems and their payloads have been highly proprietary and mission-specific. While some systems offer swappable payloads, these are rarely interchangeable across different manufacturers, leading to “vendor lock.” If a unit requires a different kinetic effect, it is often forced to procure an entirely new drone system from the original manufacturer.¹¹

5.1. The Modular Open Systems Approach (MOSA)

The strategic solution to this bottleneck is the enforcement of a Modular Open Systems Approach (MOSA). MOSA is a technical and business strategy that adopts open standards to create highly cohesive, loosely coupled system structures.¹⁰ By standardizing the interfaces between the vehicle and the payload, the DoD can stimulate intense competition among sub-tier suppliers. Small, specialized tech firms can design innovative micro-munitions or sensors without needing to engineer a flight-capable drone, while airframe manufacturers can focus on range, endurance, and cost-efficiency.³⁷

MOSA adoption is a key focus driven by the National Defense Authorization Act, establishing legal requirements under Title 10 U.S. Code 2446a.(b).¹⁰ Existing standards under the MOSA umbrella include Open Mission Systems (OMS) for aviation weapons, Future Airborne Capability Environment (FACE) for software, and Weapon Open Systems Architecture (WOSA) for munitions development.³⁸

5.2. Standardization Interfaces: Picatinny CLIK and Mod Payload

Translating MOSA from concept to physical reality requires exacting engineering standards specifically tailored for uncrewed platforms. Two prominent developments are shaping the weaponization of uncrewed fleets:

• Picatinny Common Lethality Integration Kit (CLIK): Developed by the DEVCOM Armaments Center, the Picatinny CLIK specification establishes a universal standard for weaponizing sUAS. In the same way the Picatinny Rail standardized rifle accessories, CLIK explicitly defines the physical mechanical attachment, the electrical power and network interfaces, and the safety-critical architecture required between the ground control station, the drone, and the lethal payload.¹¹ By adhering to this standard, warfighters can swap payloads on the battlefield using common connections, adapting COTS drones into strike assets. The goal is to eliminate unique integration methods and costly acquisition conditions created by proprietary designs.¹¹
• Mod Payload Standard: Managed by a government and industry team led by the Johns Hopkins Applied Physics Laboratory (JHU APL), this standard focuses on true plug-and-play interoperability for electronic warfare, signals intelligence, and communications payloads.⁴² The latest update, revision 6.1, expands Mod Payload to unmanned surface vehicles (USVs) and dismounted personnel, streamlining access for industry and allied partners.⁴²

The operational impact of these standards is already visible. For example, systems like the AeroVironment VAPOR CLE helicopter UAS utilize the CLiK interface to integrate modular lethal payloads, including 60mm/81mm mortar conversion kits and 40mm munitions.⁴³ Saab and other defense contractors are developing adaptable warheads designed to insert into loitering munitions to optimize effects against specific targets.⁴⁴ This paradigm shift ensures that as new, highly effective energetics or warhead designs are developed, they can be immediately fielded across the existing fleet of diverse drones without requiring platform redesigns.⁴¹

6. Expeditionary Logistics and Distributed Rearming

The procurement of munitions is only the preliminary challenge; delivering, storing, and loading those munitions onto drone platforms in contested, distributed environments presents an equally daunting systemic hurdle. Current U.S. operational concepts for peer conflict, specifically Distributed Maritime Operations (DMO), Expeditionary Advanced Base Operations (EABO), and Littoral Operations in a Contested Environment (LOCE), mandate that forces disperse across vast geographic areas—such as the archipelagos of the Indo-Pacific—to complicate adversary targeting.¹²

6.1. The Tyranny of Distance and Austere Storage

DMO and EABO fundamentally disrupt traditional logistical models. Large, centralized supply depots and established field trains present unacceptably massive targets for adversary long-range precision fires and loitering munitions.¹⁵ Historically, logistical responses relied on a “hub-and-spoke” framework, where large aircraft or ships delivered supplies to a central node, and smaller assets distributed them outward.⁴⁷ In a contested environment saturated with intelligence, surveillance, and reconnaissance (ISR) drones, this massing of sustainment assets close to the forward line of troops guarantees rapid attrition.¹⁵

Consequently, forces must operate from temporary, austere locations. This dispersion creates severe challenges for the storage and handling of explosive munitions. Ammunition storage is governed by stringent safety regulations, such as the Defense Explosives Safety Regulation (DESR 6055.09) and DDESB standards.⁴⁸ These regulations mandate specific asset preservation distances and minimum separation distances to prevent catastrophic chain reactions in the event of an incident or attack.⁵⁰ On small, non-contiguous terrain features or littoral islands, adhering to these explosive safety footprints while maintaining a concealed, low-signature posture is exceptionally difficult.⁵¹ The time-space challenge of separated units requires additional distribution capacity to ensure constant, concealed deliveries without creating targetable supply dumps.⁵²

6.2. Rearming at Sea: The TRAM Initiative

For maritime operations, a fleet dispersed for DMO expends its vertical launch system (VLS) munitions rapidly. By dispersing combat power beyond carriers to destroyers and frigates, the Navy forces adversaries to search wider areas, but this also distributes the demand for munitions.¹³ Historically, once a surface combatant depleted its VLS cells, the warship had to withdraw from the theater and travel long distances to a secure port to reload, removing critical combat power from the fight and exposing the vessel during transit.⁵⁴

To counter this, the Navy has prioritized the Transferable Reload At-sea Method (TRAM). Recently demonstrated off the coast of California, TRAM enables cruisers and destroyers to rearm their MK 41 VLS canisters while underway, connecting to Military Sealift Command dry cargo ships in the open ocean.⁵⁴ During the demonstration, the USS Chosin teamed up with the USNS Washington Chambers to transport and load a missile canister using the TRAM device along rails connected to the VLS modules.⁵⁴ By fielding TRAM within the next two to three years, the Navy will maintain persistent forward-strike capacity, effectively keeping distributed assets in the fight without severing their logistical tethers.⁵⁴

In contested environments, traditional ‘hub-and-spoke’ logistics are replaced by dynamic resupply networks. TRAM allows underway reloading of warships, while uncrewed logistics systems (ULS-A) distribute precision payloads to decentralized island outposts, circumventing centralized depots entirely.

6.3. Uncrewed Logistics and the “Zero Line”

Resupplying the “zero line” or Forward Line of Troops (FLOT) has become exceptionally lethal due to ubiquitous adversary ISR and drone saturation.¹⁶ To mitigate the risks of moving heavy logistical convoys, the DoD is developing Unmanned Logistics Systems-Air (ULS-A) and Unmanned Ground Vehicles (UGVs) to execute tactical resupply.⁵⁹

These autonomous logistical platforms can move ammunition, batteries, and drone payloads to distributed units across non-contiguous terrain without risking human crews.⁴⁶ The Marine Corps Aviation Plan highlights the necessity of vertical and connected replenishment from Combat Logistic Fleet vessels to support distributed aviation operations.⁶² Furthermore, research is advancing toward automated rearming systems, where a large UGV can carry fuel and munitions to automatically launch, recover, and rearm smaller vertical take-off and landing (VTOL) drones at forward locations.⁶³ This extends the operational reach of the drone fleet while keeping human operators safely distanced from the launch signature, a concept critical to controlling the “atmospheric littoral”—the low-altitude airspace that enhances ground maneuverability.⁶³

However, the realization of large-scale autonomous ground vehicle operations remains challenging. While programs like DARPA’s RACER (Robotic Autonomy in Complex Environments with Resiliency) have demonstrated successful autonomous breaching exercises using modified Textron Ripsaw M5 vehicles, widespread operational deployment is estimated to be years away, hindered by undefined requirements and the complexities of off-road autonomy.⁶¹

7. Scaling Production: From Artisanal Assembly to Mass Output

The ultimate test of the defense industrial base is the transition from low-rate initial production—often characterized by artisanal, highly manual assembly—to rapid, automated mass output. Current Western munitions stockpiles, optimized for low-intensity conflicts over the last two decades, are widely considered insufficient for a sustained peer conflict.⁶⁵

7.1. The Cost and Rate Paradigm

Traditional precision-guided munitions (PGMs) are exquisite, highly effective, and exceedingly expensive to produce. For instance, a single Patriot PAC-3 MSE interceptor costs approximately $3.9 million, while a THAAD interceptor costs $15.5 million.⁶⁵ These systems require years of lead time from contract award to delivery, meaning depleted stockpiles cannot be quickly replenished.⁶⁵ In contrast, the operational environment demands high-volume, low-cost offensive capabilities that can overwhelm defensive systems through sheer numbers—a concept referred to as the “Uberization of warfare”.¹⁸

Loitering munitions bridge this gap by compressing the kill chain into a single, expendable platform that combines the airframe, the sensor, and the warhead.²¹ They provide a cost-effective alternative to multi-million-dollar PGMs, freeing up exquisite systems for high-value targets while utilizing affordable mass to strike dispersed armor and personnel.²⁴ As noted in recent analyses, the ability to strike with precision from a distance is no longer reserved for superpowers; low-cost long-range precision weapons like the Shahed 136 have revolutionized strike dynamics, initiating an arms race for the least expensive precision systems.⁶⁸

7.2. Industrial Surge Examples

Achieving mass requires unprecedented scaling efforts by industry partners. AeroVironment, a primary producer of loitering munitions such as the Switchblade series, provides a current case study in industrial surging. Recognizing the anticipated demand driven by global conflicts and DoD initiatives like the Low Altitude Stalking and Strike Ordnance (LASSO) program, the manufacturer accelerated production of the Switchblade 600 from 40 systems per month to 240 systems per month.⁶⁹

To prepare for future demands, the company is investing in a next-generation manufacturing facility in Salt Lake City, Utah, intended to boost capacity to over 1,200 units per month, or roughly 14,400 drones annually.⁷⁰ This expansion comes alongside significant DoD contracts, including a $186 million delivery order for Switchblade 600 Block 2 and 300 Block 20 systems equipped with explosively formed penetrator (EFP) payloads.⁷¹

Simultaneously, munitions like the GBU-69/B Small Glide Munition, engineered for precision strikes with a substantial blast-fragmentation warhead, are being integrated across uncrewed platforms like the MQ-1C Gray Eagle and MQ-9A Reaper.⁷² Developed by Dynetics and USSOCOM, the SGM represents a tailored approach to equipping platforms with standoff precision capabilities, though procurement scaling must continuously align with future conflict priorities.⁷³

7.3. Strategic Frameworks for Resilience

To support these industrial surges and mitigate vulnerabilities, the DoD is implementing the National Defense Industrial Strategy (NDIS). This strategy, and its associated Implementation Plan, details actions to build resilience, reshore critical supply chains, and foster advanced manufacturing techniques to ensure that the capacity to build munitions matches the strategic imperative to employ them.⁷⁴ This includes specific funding through the Defense Production Act Title III, Industrial Base Analysis and Sustainment, and investments in munitions production to secure supply chains.⁷⁴

8. Strategic Recommendations for DoD Leadership

The Department of Defense’s investments in uncrewed technologies risk profound operational underperformance if the platforms arrive at the tactical edge without the necessary kinetic payloads. To ensure warfighters possess the required kinetic effects in a peer conflict, DoD leadership must address the systemic requirements of the munition supply chain with the same urgency applied to drone acquisition.

The analysis yields the following strategic imperatives:

1. Map and Secure Sub-Tier Dependencies: The DoD must gain comprehensive visibility into the tier-three and tier-four suppliers of critical materials. Action is required to secure the supply of Gallium-Nitride for datalinks, specialized semiconductors, and the precursor chemicals required for advanced energetics. Furthermore, investments must be directed to reshore or “friend-shore” the processing of Neodymium-Iron-Boron magnets and the manufacturing of mini-turbojet engines, which currently present severe bottlenecks in the production of high-speed loitering munitions.
2. Mandate Open Architecture for Payloads: Initiatives like Replicator must strictly enforce Modular Open Systems Approaches (MOSA) across all procured platforms. By mandating adherence to interface standards such as the Picatinny CLIK and Mod Payload, the DoD can ensure that any procured sUAS can natively accept a wide variety of modular warheads and sensors. This effectively eliminates vendor lock, allowing the munitions industrial base to innovate and scale independently of the airframe manufacturing base.
3. Accelerate Energetics Modernization: The 15-year Organic Industrial Base Modernization Plan is a necessary endeavor, but its timeline is misaligned with the immediate threat environment. The DoD must accelerate the transition away from antiquated chemical processes by stimulating private capital and expanding public-private partnerships, such as the Munitions Campus model. Clustering the production of specialized propellants, solid rocket motors, and explosive compounds will reduce supply chain friction and scale output. Additionally, concerted efforts must continue through ManTech to address the critical workforce deficits in advanced manufacturing.
4. Integrate Rearming Logistics into Platform Procurement: A drone fleet is only as effective as its reload capacity. As the Joint Force embraces Distributed Maritime Operations and Expeditionary Advanced Base Operations, the logistics of rearming must be treated as a primary warfighting function. Continued investment in at-sea reloading mechanisms like TRAM is essential to sustain naval strike power. Simultaneously, the development and fielding of uncrewed logistics systems (ULS-A and UGVs) must be accelerated to safely distribute containerized payloads and rearm platforms at the austere, dispersed locations mandated by modern operational concepts.

The tendency to fixate on the technology of the drone itself obscures the reality that an uncrewed system is merely a delivery mechanism. The true center of gravity in autonomous warfare is the industrial capacity to mass-produce, securely transport, and reliably integrate the miniaturized precision munitions that deliver the decisive tactical effect. Scaling the fleet without concurrently scaling the specialized munitions supply chain will yield a force that is technologically advanced, but kinetically hollow.

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Sources Used

1. Office of the Under Secretary of Defense (Comptroller)/Chief …, accessed April 24, 2026, https://comptroller.war.gov/portals/45/Documents/defbudget/FY2025/FY2025_Weapons.pdf
2. DOD moves to make its largest-ever investment in drones and anti-drone weapons, accessed April 24, 2026, https://defensescoop.com/2026/04/21/dod-plans-largest-ever-investment-drones-anti-drone-weapons/
3. Deputy Secretary of Defense Kathleen Hicks Announces Additional …, accessed April 24, 2026, https://www.war.gov/News/Releases/Release/Article/3963289/deputy-secretary-of-defense-kathleen-hicks-announces-additional-replicator-all/
4. Replicator: A Bold New Path for DoD | Center for Security and Emerging Technology %, accessed April 24, 2026, https://cset.georgetown.edu/article/replicator-a-bold-new-path-for-dod/
5. Replicator Initiative Looks to Swarm Through ‘Valley of Death’ – National Defense Magazine, accessed April 24, 2026, https://www.nationaldefensemagazine.org/articles/2024/1/4/replicator-initiative-looks-to-swarm-through-valley-of-death
6. Replicator: An inside look at the Pentagon’s ambitious drone program – Defense News, accessed April 24, 2026, https://www.defensenews.com/pentagon/2023/12/19/replicator-an-inside-look-at-the-pentagons-ambitious-drone-program/
7. The Drone Supply Chain War: Identifying the Chokepoints to Making …, accessed April 24, 2026, https://www.csis.org/analysis/drone-supply-chain-war-identifying-chokepoints-making-drone
8. At a Glance: the U.S. Defense Industrial Base – War on the Rocks, accessed April 24, 2026, https://warontherocks.com/cogs-of-war/at-a-glance-the-u-s-defense-industrial-base/
9. Characterizing the Uncrewed Systems Industrial Base | RAND, accessed April 24, 2026, https://www.rand.org/pubs/research_reports/RRA1474-1.html
10. MOSA | NAVAIR, accessed April 24, 2026, https://www.navair.navy.mil/MOSA
11. Modular Payloads for UAS – Army SBIR|STTR Program, accessed April 24, 2026, https://armysbir.army.mil/topics/modular-payloads-for-uas/
12. NOT FOR PUBLICATION UNTIL RELEASED BY THE HOUSE ARMED SERVICES COMMITTEE STATEMENT OF VICE ADMIRAL RICK L. WILLIAMSON, DEPUTY C, accessed April 24, 2026, https://docs.house.gov/meetings/AS/AS03/20211202/114276/HHRG-117-AS03-Wstate-WilliamsonR-20211202.pdf
13. Distributed Maritime Operations, Logistics, Industry, and American Strategy in Asia, accessed April 24, 2026, https://www.militarystrategymagazine.com/article/distributed-maritime-operations-logistics-industry-and-american-strategy-in-asia/
14. Expeditionary Advanced Base Operations (EABO) Handbook Considerations for Force Development and Employment 1 June 2018 Version 1.1 – Marine Corps Association, accessed April 24, 2026, https://www.mca-marines.org/wp-content/uploads/Expeditionary-Advanced-Base-Operations-EABO-handbook-1.1.pdf
15. Utilization of Unmanned Systems to Increase the Survivability of the Field Artillery, accessed April 24, 2026, https://www.lineofdeparture.army.mil/Journals/Field-Artillery/Field-Artillery-Archive/Field-Artillery-2025-E-Edition/Utilization-of-Unmanned-System-Field-Artillery/
16. Contested Logistical Resupply to the Zero Line: How Drones and Signals Require a Change in Standard Operating Procedures – Small Wars Journal, accessed April 24, 2026, https://smallwarsjournal.com/2025/11/24/contested-logistical-resupply-to-the-zero-line-how-drones-and-signals-require-a-change-in-standard-operating-procedures/
17. Forging America’s 21st Century Defense Industrial Base: Applying Lessons from the Arsenal of Democracy to Modern Great-Power Competition – U.S. Army, accessed April 24, 2026, https://www.army.mil/article/288967/forging_americas_21st_century_defense_industrial_base_applying_lessons_from_the_arsenal_of_democracy_to_modern_great_power_competition
18. The Impact of Drones on the Battlefield: Lessons of the Russia-Ukraine War from a French Perspective | Hudson Institute, accessed April 24, 2026, https://www.hudson.org/missile-defense/impact-drones-battlefield-lessons-russian-ukraine-war-french-perspective-tsiporah-fried
19. The Missile and Drone Dilemma: When Defensive Measures Outstrip the Cost of Attack, accessed April 24, 2026, https://www.habtoorresearch.com/programmes/the-missile-and-drone-dilemma-when-defensive-measures-outstrip-the-cost-of-attack/
20. The U.S. Defense Industrial Base: Past Strength, Current Challenges, and Needed Change, accessed April 24, 2026, https://www.heritage.org/military-strength/topical-essays/the-us-defense-industrial-base-past-strength
21. Loitering munitions explained | Unmanned Aerial Weapons – Maris Tech, accessed April 24, 2026, https://www.maris-tech.com/blog/loitering-munitions-a-complete-guide-to-unmanned-aerial-weapons-explosive-uavs/
22. Ukraine’s drone attack fleet is facing a shortage of mini jet engines – Marine Link, accessed April 24, 2026, https://www.marinelink.com/blogs/blog/ukraines-drone-attack-fleet-is-facing-a-shortage-of-mini-jet-104486
23. Ukraine’s attack drone fleet faces a mini jet engine supply crunch – KFGO, accessed April 24, 2026, https://kfgo.com/2026/04/07/ukraines-attack-drone-fleet-faces-a-mini-jet-engine-supply-crunch/
24. Europe’s mini-jet engine bottleneck is constraining Ukraine’s deep-strike drone programme, accessed April 24, 2026, https://defencematters.eu/europes-mini-jet-engine-bottleneck/
25. Leveraging Digital Engineering to Modernize Munition Production | Article – U.S. Army, accessed April 24, 2026, https://www.army.mil/article/290073/leveraging_digital_engineering_to_modernize_munition_production
26. Energetics Production Modernization Faces Cultural, Technical Hurdles, accessed April 24, 2026, https://www.nationaldefensemagazine.org/articles/2025/12/9/energetics-production-modernization-faces-cultural-technical-hurdles
27. NATIONAL ENERGETICS PLAN, accessed April 24, 2026, https://www.nacconsortium.org/wp-content/uploads/2023/08/National_Energetics-Plan_DRAFT_DISTRO_A.pdf
28. Wittman: Modern Conflicts Demand Modern Munitions—Not Yesterday’s Defense Acquisition Processes | House Armed Services Committee, accessed April 24, 2026, https://armedservices.house.gov/news/documentsingle.aspx?DocumentID=5198
29. Army advances 15-year OIB modernization plan | Article | The United States Army, accessed April 24, 2026, https://www.army.mil/article/288829/army_advances_15_year_oib_modernization_plan
30. Army completes first year of modernization plan | Article | The United States Army, accessed April 24, 2026, https://www.army.mil/article/280158/army_completes_first_year_of_modernization_plan
31. Department of War Announces Groundbreaking of New Munitions Campus in Indiana, accessed April 24, 2026, https://www.war.gov/News/Releases/Release/Article/4411124/department-of-war-announces-groundbreaking-of-new-munitions-campus-in-indiana/
32. Advanced Manufacturing Training Grant Program | CAM, accessed April 24, 2026, https://cam.masstech.org/advanced-manufacturing-training-grant
33. DoW ManTech – Home, accessed April 24, 2026, https://www.dodmantech.mil/
34. ARM Institute Publishes New Workforce Training Gap Analysis Report | Manufacturing USA, accessed April 24, 2026, https://www.manufacturingusa.com/news/arm-institute-publishes-new-workforce-training-gap-analysis-report
35. ARM Institute Releases Workforce Training Gap Analysis, accessed April 24, 2026, https://arminstitute.org/news/fow-training-gap/
36. Grant Solicitation for the Advanced Manufacturing Training Program | NEMC, accessed April 24, 2026, https://nemicroelectronics.org/grant-solicitation-advanced-manufacturing-training-program
37. Modular Open Systems Approach – DoW Research & Engineering, OUSW(R&E), accessed April 24, 2026, https://www.cto.mil/sea/mosa/
38. What is MOSA? – BAE Systems, accessed April 24, 2026, https://www.baesystems.com/en-us/definition/what-is-mosa
39. Uncrewed Aerial System (UAS) Munition Payload Interface Solution – Sources Sought, accessed April 24, 2026, https://sam.gov/workspace/contract/opp/93c9e4e6074e4013896dc23ebc0df492/view
40. DESIGN STANDARD FOR Picatinny Common Lethality Integration …, accessed April 24, 2026, https://aal.mil/assets/files/pdf/picatinny-clik-design-standard.pdf
41. Lethal unmanned aerial systems: Safe, reliable, lethal armaments capability at every echelon | Article | The United States Army, accessed April 24, 2026, https://www.army.mil/article/286795/lethal_unmanned_aerial_systems_safe_reliable_lethal_armaments_capability_at_every_echelon
42. Design Standard Update Improves Modular Architecture for Unmanned Platforms, accessed April 24, 2026, https://www.jhuapl.edu/news/news-releases/250805-mod-payload
43. The VAPOR® CLE sets a new standard for Group 2 unmanned …, accessed April 24, 2026, https://www.avinc.com/images/uploads/product_docs/Vapor_CLE_Datasheet.pdf
44. Warheads and Mortar Ammunition | Saab, accessed April 24, 2026, https://www.saab.com/products/warheads
45. Warheads for UAVs and loitering munitions – YouTube, accessed April 24, 2026, https://www.youtube.com/watch?v=lS-1KVWcnpQ
46. Distributed Operations Require Small Platforms to Distribute Logistics – National Defense Transportation Association, accessed April 24, 2026, https://www.ndtahq.com/distributed-operations-require-small-platforms-to-distribute-logistics/
47. The Last Mile Problem: Re-Thinking Modern Aerial Logistics – ParaZero Technologies, accessed April 24, 2026, https://parazero.com/2025/11/11/the-last-mile-problem-re-thinking-modern-aerial-logistics/
48. UFC 4-420-01 Ammunition and Explosive Storage Magazines – Whole Building Design Guide, accessed April 24, 2026, https://www.wbdg.org/FFC/DOD/UFC/ufc_4_420_01_2025.pdf
49. BY ORDER OF THE SECRETARY DESR 6055.09_DAFMAN91-201 OF THE AIR FORCE 18 JUNE 2025 Safety EXPLOSIVES SAFETY STANDARDS COMPLIANCE, accessed April 24, 2026, https://static.e-publishing.af.mil/production/1/af_se/publication/desr6055.09_dafman91-201/desr6055.09_dafman91-201.pdf
50. Wartime Storage | Munitions Safe Storage, Operation Essential in War, Peace – U.S. Army, accessed April 24, 2026, https://www.army.mil/article/265889/wartime_storage_munitions_safe_storage_operation_essential_in_war_peace
51. Tentative Manual For Expeditionary Advanced Base Operations 2nd Edition – Marines.mil, accessed April 24, 2026, https://www.marines.mil/Portals/1/Docs/230509-Tentative-Manual-For-Expeditionary-Advanced-Base-Operations-2nd-Edition.pdf
52. Evaluating the Logistical Supportability of Expeditionary Advanced Base Operations – DTIC, accessed April 24, 2026, https://apps.dtic.mil/sti/trecms/pdf/AD1144374.pdf
53. TENTATIVE MANUAL FOR EXPEDITIONARY ADVANCED BASE OPERATIONS – Marine Corps Association, accessed April 24, 2026, https://www.mca-marines.org/wp-content/uploads/TM-EABO-First-Edition-1.pdf
54. ‘Game changing’: Navy reloads cruiser’s missiles at sea for first time – Navy Times, accessed April 24, 2026, https://www.navytimes.com/news/your-navy/2024/10/16/game-changing-navy-reloads-cruisers-missiles-at-sea-for-first-time/
55. Navy Demonstrates First At-sea Reloading of Vertical Launching System, accessed April 24, 2026, https://www.navy.mil/Press-Office/News-Stories/Article/3935108/navy-demonstrates-first-at-sea-reloading-of-vertical-launching-system/
56. Navies and reloads: no silver bullet? – The International Institute for Strategic Studies, accessed April 24, 2026, https://www.iiss.org/online-analysis/military-balance/2024/10/navies-and-reloads-no-silver-bullet/
57. Navy Demonstrates ‘Game-Changing’ System to Rearm Warships at Sea – DLA, accessed April 24, 2026, https://www.dla.mil/About-DLA/News/News-Article-View/Article/3861597/navy-demonstrates-game-changing-system-to-rearm-warships-at-sea/
58. Is drone-based resupply viable? – European Security & Defence, accessed April 24, 2026, https://euro-sd.com/2025/10/articles/armament/47250/is-drone-based-resupply-viable/
59. How unmanned systems are reshaping logistics in contested environments, accessed April 24, 2026, https://breakingdefense.com/2026/01/how-unmanned-systems-are-reshaping-logistics-in-contested-environments/
60. Unmanned Logistics Systems – Air – NAVAIR, accessed April 24, 2026, https://www.navair.navy.mil/product/Unmanned-Logistics-Systems-Air
61. Army Still Years Away From Large-Scale Autonomous Ground Vehicle Ops (UPDATED), accessed April 24, 2026, https://www.nationaldefensemagazine.org/articles/2026/2/12/army-still-years-away-from-large-scale–autonomous-ground-vehicle-ops
62. 2025 Marine Aviation Plan, accessed April 24, 2026, https://media.defense.gov/2025/mar/12/2003665702/-1/-1/1/2025-marine-corps-aviation-plan.pdf
63. Automated Launch, Recovery, and Refueling for Small Unmanned Aerial Vehicles – DTIC, accessed April 24, 2026, https://apps.dtic.mil/sti/tr/pdf/ADA477747.pdf
64. Recoverable Loitering Munitions Are More Cost – and Mission-Effective Than One-Way Attack Drones, Says New Teledyne FLIR Defense Whitepaper, accessed April 24, 2026, https://defense.flir.com/about/news/recoverable-loitering-munitions/
65. Last Rounds? Status of Key Munitions at the Iran War Ceasefire – CSIS, accessed April 24, 2026, https://www.csis.org/analysis/last-rounds-status-key-munitions-iran-war-ceasefire
66. BEYOND PRECISION – Center for Strategic and Budgetary Assessments | CSBA, accessed April 24, 2026, https://csbaonline.org/uploads/documents/Beyond_Precision_Report_CSBA8355_FINAL_web.pdf
67. Loitering munition – Wikipedia, accessed April 24, 2026, https://en.wikipedia.org/wiki/Loitering_munition
68. Cheaper Precision Weapons: An Exploratory Study about the HESA Shahed 136, accessed April 24, 2026, https://www.scirp.org/journal/paperinformation?paperid=131823
69. AV Unveils Next Generation of Switchblade® Loitering Munitions – AeroVironment, accessed April 24, 2026, https://www.avinc.com/2025/10/13/av-unveils-next-generation-of-switchblade-loitering-munitions/
70. Switchblade Production Rates, Lag AeroVironment Moves to Fix it – Defense Express, accessed April 24, 2026, https://en.defence-ua.com/industries/switchblade_production_rates_lag_aerovironment_moves_to_fix_it-16146.html
71. AV Receives $186 Million U.S. Army Delivery Order for Next-Generation Switchblade Systems – AeroVironment, Inc., accessed April 24, 2026, https://www.avinc.com/resources/press-releases/view/av-receives-186-million-u.s-army-delivery-order-for-next-generation-switchblade-systems
72. Dynetics GBU-69/B SGM – Designation-Systems.Net, accessed April 24, 2026, https://www.designation-systems.net/dusrm/app5/sgm.html
73. WEAPONS & PLATFORMS – Air & Space Forces Magazine, accessed April 24, 2026, https://www.airandspaceforces.com/app/uploads/2023/06/Weapons_Platforms_0623.pdf
74. NDIS Implementation Plan ii – GovInfo, accessed April 24, 2026, https://www.govinfo.gov/content/pkg/GOVPUB-D-PURL-gpo234260/pdf/GOVPUB-D-PURL-gpo234260.pdf
75. DOD Lays Out Plan to Implement National Defense Industrial Strategy – Department of War, accessed April 24, 2026, https://www.war.gov/News/News-Stories/Article/Article/3949630/dod-lays-out-plan-to-implement-national-defense-industrial-strategy/
76. Implementing the National Defense Industrial Strategy: Issues for Congress – EveryCRSReport.com, accessed April 24, 2026, https://www.everycrsreport.com/reports/IN12459.html
77. DOD Official: Defense Industrial Strategy Already Making Headway in Maritime Space, accessed April 24, 2026, https://www.war.gov/News/News-Stories/Article/article/3739030/dod-official-defense-industrial-strategy-already-making-headway-in-maritime-spa/

1. Executive Summary

The Department of Defense (DoD) is entering a critical, transformative juncture in its acquisition, deployment, and tactical integration of unmanned aerial systems (UAS). Driven by executive mandates and rapid acquisition initiatives such as Swarm Forge and the strategic push to field upwards of 300,000 low-cost, attritable drones, the United States military is proposing unprecedented financial and structural investments in autonomous platforms.¹ The fiscal year 2027 budget request alone allocates an estimated $70 billion for drone and counter-drone technologies, signaling a profound shift in modern warfighting.³ However, the strategic discourse surrounding this massive expansion has overwhelmingly, and perilously, centered on platform procurement, hardware specifications, and raw artificial intelligence capabilities. This inherently hardware-centric focus severely overlooks the most critical, vulnerable, and systemic requirement within the unmanned operational ecosystem: the human operator.

As the tactical paradigm shifts aggressively from single-platform manual control to the deployment of massive, semi-autonomous swarms, the human nervous system remains the ultimate operational bottleneck. Operators are increasingly subjected to task saturation, cognitive lockup, and decision paralysis, which effectively negate the tactical advantages of advanced, high-speed platforms.⁴ The psychological and neurological load of managing multiple autonomous agents simultaneously extends far beyond traditional physical fatigue. It manifests in degraded situational awareness, delayed decision-making, severe attentional blinding, and historically high rates of emotional burnout and moral injury.⁶

To successfully enable warfighters in this new era of distributed lethality, DoD leadership must pivot decisively from treating unmanned operations as a mere extension of traditional crewed aviation. This requires a systemic overhaul in two primary areas of development. First, there must be a fundamental redesign of Human-Machine Interfaces (HMI) to accommodate multi-vehicle supervisory control, shifting away from raw data feeds toward ecological interface designs and adaptive neurotechnology.⁸ Second, there must be a foundational doctrinal shift in operator training and career management, transitioning personnel from a traditional “pilot” mindset—focused on kinesthetic control and single-platform stability—to a “fleet manager” mindset focused on networked orchestration and macro-cognitive resource management.⁸ This strategic report details the physiological limitations of human operators, the engineering requirements for next-generation HMIs, the sustainment realities of massive drone fleets, and the systemic ecosystem adjustments necessary to realize the full potential of human-machine integrated formations.

2. The Strategic Context: Drone Dominance and the Transformation Gap

The DoD’s push toward total drone dominance is rooted in the recognition that future conflicts will be characterized by distributed, resilient, and highly data-driven networks. This operational concept, often referred to as the “kill web,” replaces the traditional, linear “kill chain” (find, fix, track, target, engage, assess) with a dynamic environment where any sensor can inform any shooter.¹¹ The transition demands that platforms function as flying information systems rather than isolated strike vehicles. However, realizing this vision requires more than just purchasing advanced airframes.

2.1 The Hardware Bias and Ecosystem Immaturity

Current military acquisition models consistently prioritize the rapid procurement of platforms, often neglecting the underlying sustainment, training, and cognitive infrastructure required to field them effectively. Historical aviation data demonstrates a standard five-to-ten-year “transformation gap” between the initial introduction of a new platform and the actual maturation of its supporting operational ecosystem.¹² For example, advanced platforms like the V-22 Osprey and the F-35 Lightning II only achieved their true transformational potential roughly eight years after entering service. This occurred only when military branches adapted their ground-level tactics and conceptually reframed the aircraft as integrated network nodes rather than straightforward replacements for legacy rotary or fighter systems.¹²

Similarly, the U.S. Navy fielded the T-6B trainer with a modern glass cockpit, yet did not routinely exploit its heads-up display (HUD) for approximately 15 years because the “mental furniture” and syllabus design of the training community had not yet caught up to the hardware.¹² The DoD is currently attempting to compress this historical timeline drastically. The Swarm Forge initiative, managed by the Chief Digital and Artificial Intelligence Office (CDAO), aims to deliver validated swarm packages in 90 days or less, featuring heterogeneous autonomy from multiple vendors to avoid single-vendor lock-in.¹

While this rapid iteration is necessary to combat evolving geopolitical threats and maintain technological parity, deploying thousands of systems without a concurrent evolution in human interface design and ecosystem support creates a severe operational vulnerability.

The hardware is advancing at a digital-age pace, but the cognitive frameworks and institutional mechanisms required to supervise these systems remain entrenched in industrial-age methodologies. The absence of integrated doctrine, training, and operational concepts for large-scale robotic employment leaves the joint force at risk of strategic and tactical disadvantage, regardless of the sheer volume of drones procured.¹

2.2 Operational Requirements for Drone Swarms

The Pentagon’s vision for drone swarms, as articulated in upcoming Crucible events, mandates highly specific operational requirements that place immense pressure on human operators if not properly abstracted. These swarms must include a minimum of four unmanned aerial systems operating simultaneously, demonstrating end-to-end autonomous completion of complex mission sets such as intelligence, surveillance, and reconnaissance (ISR), or active targeting under the “Find, Fix, Finish” concept.¹

These swarms are required to utilize AI agents capable of autonomously coordinating efforts and assigning roles among the robotic systems. The architecture must feature decentralized control to prevent single points of failure, ensuring the swarm remains highly functional even if individual systems are lost in combat or disrupted by electronic warfare.¹ The platforms must be equipped with automatic target recognition (ATR) and machine learning capabilities that allow for dynamic, in-field learning and adaptive behavior based on real-time environmental feedback.¹

Crucially, the systemic requirements specify that there should be minimal operator intervention required for swarm control, yet the systems must rigorously remain under “meaningful human command”.¹ This paradox—requiring the human to be simultaneously hands-off yet firmly in command—is the central challenge of multi-UAS operations. It requires the operator to maintain perfect situational awareness of a highly complex, decentralized, and autonomous process, ready to intervene at a moment’s notice, without being overwhelmed by the data stream.

3. The Sustainment Paradox: Infrastructure vs. Attritable Hardware

Before addressing the cognitive load on the operator, it is imperative to understand the physical and logistical load placed on the operational ecosystem. The operational reality of large-scale combat operations (LSCO) introduces a severe paradox: battlefield capability without the resilient means to sustain it becomes a strategic liability, not an advantage.¹³

3.1 The Logistics Tail of Autonomous Fleets

Modern mobile brigade combat teams (MBCTs) rely heavily on commercial off-the-shelf (COTS) systems to fill critical operational gaps. These include first-person view (FPV) drones, modular power sources, and light vehicles.¹³ While these systems reflect a push toward agility, they introduce deep logistical fragmentation. Many of these systems lack full Class IX (repair parts) integration within standard military supply chains and require proprietary civilian vendor support to repair or replace components.¹³

A buildup of tens or hundreds of thousands of attritable drones will create an unprecedented sustainment burden across the force.¹⁴ Drones are not inert munitions; batteries expire, sensitive electro-optical sensors require calibration and replacement, supply chains for microchips fluctuate, and drones stored in uncontrolled or austere environments deteriorate quickly.¹⁴ Even if the platforms themselves are designed to be attritable, the sustainment system behind them will demand significant manpower, specialized diagnostic tools, controlled warehouse space, and rigorous processes for tracking and end-of-service disposal.¹⁴

3.2 Operating and Support Cost Escalation

The financial reality of this sustainment burden is already becoming apparent in legacy systems. The Department of Defense identified 14 distinct weapon systems with critical operating and support (O&S) cost growth during sustainment reviews conducted for fiscal years 2023 and 2024.¹⁵ Critical O&S cost growth represents at least a 25 percent increase in the cost estimate for the remainder of a system’s life cycle compared to baseline independent estimates.¹⁵

This cost growth is frequently driven by extensions to operational life and the failure to implement iterative, fleet-wide software and hardware updates. For example, a Government Accountability Office (GAO) report noted that failing to complete a software update for all units of a combat vehicle weapon system resulted in massive inefficiencies; completing that single software update across the fleet could save over $130 million and ensure effective operation over a 30-year span.¹⁵ If the DoD applies its current, fragmented sustainment approach to a fleet of 300,000 drones, the resulting O&S costs will rapidly eclipse the initial procurement budget, draining resources away from combat effectiveness and operator training.

4. Neurological Architecture and the Limits of the Human Operator

In modern drone operations—particularly in contested environments heavily saturated with electronic warfare and dynamic threats—the human mind remains the primary arbiter of mission success.⁴ Human operators face unique biological and cognitive challenges when managing robotic machines. A failure to design systems and operational tempos around these hard biological limits leads directly to mission degradation, asset loss, and fratricide.

4.1 Task Saturation and the Limits of Working Memory

When a single operator is tasked with controlling multiple unmanned vehicles, they are subjected to a continuous, unrelenting stream of visual, auditory, and telemetry data. Every minute of flight requires the operator to interpret telemetry, monitor environmental factors, manage active payloads, and communicate with ground elements.⁴ This environment demands extreme cognitive flexibility and continuous task switching.⁶

Cognitive research consistently demonstrates that human responses become substantially slower and significantly more error-prone after switching between two or more individual tasks.⁶ While an operator managing multiple vehicles may observe a greater total number of missions completed overall, this often comes at the severe expense of individual mission efficiency due to the disparate attention that must be allocated among the various assigned assets.⁶

As the number of vehicles increases, the cognitive load rapidly exceeds the operator’s working memory capacity. Working memory, governed largely by the prefrontal cortex, is responsible for keeping multiple variables actively in mind while executing complex tasks such as reasoning and learning.¹⁶ When working memory is saturated by excessive intrinsic load (the inherent complexity of multi-UAS maneuvering) and extraneous load (poorly designed interfaces, irrelevant alarms, or excessive radio chatter), the operator’s ability to process new information degrades precipitously.⁴

4.2 The Attentional Blink and Temporal Binding

This cognitive saturation often manifests neurologically as the “attentional blink.” Under conditions of rapid serial visual presentation (RSVP)—which perfectly describes a multi-display drone control station—human subjects display a severely reduced ability to report or react to a second target or critical event if it appears within 200 to 500 milliseconds of the first event.¹⁸

The attentional blink arises from the heavy demands placed on working memory encoding and response selection. When the brain processes the first piece of critical information (e.g., a surface-to-air missile lock on Drone A), it temporarily prevents high-level central resources from being applied to subsequent information (e.g., a critical battery failure on Drone B).¹⁸ In a multi-display environment where a fleet manager is monitoring high-speed drone telemetry across a swarm, this biological limitation means that cascading system failures or simultaneous threat detections will inevitably be missed by the conscious mind.

Furthermore, high-stress, high-workload environments alter the human sense of agency and temporal binding. Research involving military personnel conducting moral decision-making under high cognitive load reveals that the subjective feeling of being the author of one’s actions—a critical component for decisive action—is distorted.²⁰ When operators are overwhelmed by automation inputs or strict external orders, their sense of agency is reduced, leading to hesitation and a reliance on automated systems even when those systems are providing erroneous data.²⁰

4.3 The OODA Loop, Startle Reflex, and Decision Paralysis

Effective tactical operation relies on the continuous, rapid execution of the OODA loop: Observe, Orient, Decide, Act. High cognitive load effectively stalls this loop. When the “Orient” or “Decide” phases are delayed by massive data saturation, operators are forced to shift from proactive mission management to reactive correction, drastically increasing operational risk and lowering mission success rates.⁴

Under high-stress, unpredictable combat scenarios, this data saturation can trigger a physiological “startle reflex.” Aviation psychology identifies “cognitive lockup” as a common response to sudden, intense stressors.⁵ This occurs when an operator over-fixates on a single problem, screen, or failing drone, completely losing peripheral situational awareness and failing to see the broader tactical picture.⁵

This reaction is deeply rooted in human neurobiology. Acute stress triggers the amygdala, the brain’s threat-response center, which can effectively hijack and overpower the prefrontal cortex’s higher-order executive functions.⁵ This leads directly to tunnel vision and an absolute paralysis in analytical thinking and problem-solving capability. Research conducted by NASA psychologists indicates that physical and psychological startle responses can impair a pilot’s cognitive processing and reaction times for up to 30 seconds.⁵ In the context of drone swarm combat, where engagements are measured in milliseconds, a 30-second cognitive paralysis represents an unrecoverable operational failure.

5. Psychological Wear and Force Degradation

Beyond the immediate tactical limitations of working memory and decision paralysis, the sustained operation of remote systems inflicts significant, cumulative psychological wear on military personnel. The DoD’s transition to a massive drone fleet will fail if the workforce operating it is fundamentally compromised by fatigue and trauma.

5.1 Burnout, PTSD, and Moral Injury

Remotely piloted aircraft (RPA) operators, despite being physically removed from the kinetic dangers of the battlefield, experience high rates of psychological distress. Comprehensive reviews indicate that drone operators, intelligence coordinators, and support staff suffer from elevated rates of emotional disengagement, emotional exhaustion, burnout, and Post-Traumatic Stress Disorder (PTSD).⁷

Historically, it has been reported that RPA pilots face psychiatric risks that sometimes exceed those of crewed aircraft pilots.²¹ This is driven by the unique nature of drone warfare: the extreme intimacy of modern high-definition surveillance optics, the prolonged duration of monitoring targets, and the jarring psychological whiplash of transitioning daily between domestic family life and remote combat execution.⁷ The psychological toll is exacerbated by the sheer volume of hours spent intensely monitoring video feeds, which drains cognitive reserves and leads to severe emotional exhaustion.⁷

5.2 The “Always On” Culture and Arousal Management

The modern military operates within an “always on” culture of continuous multitasking and constant digital connectivity, which neurological science shows is highly degradative to baseline cognitive performance.²² Leaders and operators attempt to filter dozens of streams of information while operating on inadequate sleep, leading to a permanent state of cognitive fatigue.²²

Levels of emotional arousal and stress directly impact cognitive performance, following the Yerkes-Dodson Law, which identifies a “sweet spot” of stress associated with peak performance.²² The right amount of stress releases neurochemicals that generate alertness. However, chronic stress pushes operators past this optimal peak into cognitive decline. The military must evolve its culture by implementing strict cognitive fatigue management, recognizing that proper sleep and structured breaks are not luxuries, but critical variables for maintaining the processing speed and spatial awareness required for multi-UAS operations.⁴

6. Redesigning the Human-Machine Interface (HMI) for Swarm Formations

To mitigate the profound biological limitations of cognitive overload and leverage the true potential of multi-drone formations, the Human-Machine Interface must be fundamentally re-engineered. Simply porting the interface of a legacy single-drone control station (like an MQ-9 Reaper console) to a multi-monitor setup is a guaranteed path to task saturation. The interface must evolve from a manual flight control mechanism to an intelligent, adaptive supervisory system.

6.1 From Direct Control to Ecological Interface Design

The traditional 1:1 (one operator to one vehicle) or 1:N (one operator to multiple vehicles) control paradigms are proving mathematically and cognitively insufficient due to the heavy burden of maintaining adequate situational awareness across separate entities.⁶ Research indicates that an experienced operator can supervise the health and status of up to 15 UASs efficiently using moderate automation. However, when actual mission and payload management is required, a single operator’s cognitive limit is reached at approximately three systems.⁸ Beyond three systems, mission efficiency drops sharply due to task-switching costs and working memory saturation.

The solution lies in the M:N control paradigm, establishing a “Multiple Operators with Multiple UASs” (MOMU) environment where a networked team of operators shares a pool of automated assets.⁶ This architecture allows for dynamic workload distribution; if one operator becomes saturated by a complex targeting task, control of routine perimeter assets can be seamlessly handed off to another operator.⁶

To effectively support this, HMIs must employ Ecological Interface Design (EID) principles. Instead of presenting operators with overwhelming arrays of raw data feeds, altitudes, and discrete telemetry values, the HMI must abstract this information into generalized functional states.²³ By visualizing comprehensive health data, graphic trend presentations, and simplified safety-critical system states, operators can perform parallel visual searches more effectively. For instance, shifting from manual numerical checklists to digital forms with intuitive, color-coded fault indicators (e.g., orange for warning, red for critical) significantly reduces reliance on the operator’s short-term working memory and facilitates faster OODA loop processing.⁸

6.2 Automation Transparency and the Trust-Workload Tradeoff

As underlying swarm algorithms increasingly handle localized collision avoidance, route planning, and sensor fusion, the human operator transitions to a “management-by-consent” or “supervised autonomous” role. In this mode, the system analyzes data, proposes a tactical plan, and the human either approves it or intervenes by exception.⁸ However, this highly automated environment introduces deeply complex human-automation trust dynamics.

If an autonomous system is highly reliable, human operators quickly develop over-trust, exhibiting a pronounced complacency that severely diminishes their vigilance and ability to detect machine errors when they inevitably occur.²⁵ Conversely, if the system acts erratically or opaquely, operators lose trust and attempt to manually micromanage the swarm, immediately inducing task saturation and defeating the purpose of the automation.

Research into partially observable Markov decision process (POMDP) models highlights a critical transparency-workload tradeoff. Increasing the transparency of an intelligent system’s decision-making process—such as the HMI visually explaining why the drone chose a specific route or selected a specific target—increases human trust in the system. However, it simultaneously increases the human’s cognitive workload because they must read, process, and evaluate that explanation.²⁶ HMIs must dynamically balance how much “reasoning” the automation displays based on the operator’s current saturation level, providing deep transparency during low-tempo operations and abstracting it during high-intensity combat.

6.3 Neurotechnology and Adaptive Interfaces

The future of advanced HMI design relies on active physiological monitoring to create truly adaptive systems. Eye-tracking technology is proving critical in assessing mental workload in real time, far surpassing the utility of traditional self-assessment questionnaires. By analyzing gaze patterns, pupil dilation, and blink rates, systems can objectively pinpoint moments of high cognitive load or distraction.⁹ For example, decreased blink rates and erratic saccades are strong indicators of impending task saturation.⁹

When the HMI detects that an operator is approaching a cognitive breaking point, an adaptive interface can autonomously simplify data presentation, temporarily silence non-critical alarms, or alert a secondary team member in the M:N network to take over specific assets.⁹ Furthermore, integrating neurotechnology such as electroencephalography (EEG) monitoring can track frontal and parietal cortex activation. Machine learning models, such as Support Vector Machines (SVMs), can analyze alpha and beta wave ratios to assess spatial working memory load and classify attention states, allowing the control station to adapt its layout before the operator ever reaches the point of cognitive lockup.²⁸

7. Doctrinal Evolution: Transitioning from “Pilot” to “Fleet Manager”

Re-engineering the interface and the software is only half the solution; the human operator must also be re-engineered through profound doctrinal and training shifts. The traditional paradigm of military aviation places immense cultural and operational value on the “pilot”—an individual inherently focused on the kinesthetic control, aerodynamics, and stability of a single platform. Multi-UAS operations render this mindset obsolete. Operators must transition to a “fleet manager” mindset.

7.1 Redefining Operational Doctrine

The fundamental difference between managing a drone and managing a fleet is the transition from individual asset accountability to organizational, systems-level accountability.³⁰ Every drone, mission, and compliance record becomes part of a unified workflow. As flight controls become fully automated, the operator’s role shifts entirely away from flying the aircraft toward supervising networks, interpreting complex data fusion, and executing strategic oversight.⁸

This mirrors the broader tactical shift from the kill chain to the kill web. Fleet managers are no longer functioning as sequential links in a linear strike process; they are nodes of command orchestrating integrated effects across distributed domains.¹¹ A fleet manager must prioritize high-level, macro-cognitive tasks: strategic mission planning, navigating complex airspace regulations, managing proprietary supply chains, maintaining strict cyber-security over payload streams, and dynamically allocating resources under deep uncertainty.⁸

7.2 Transitioning the Workforce and Career Tracks

The Department of Defense currently possesses a vast reservoir of highly skilled remote pilots, particularly within communities operating legacy platforms like the MQ-9 Reaper. As these platforms face eventual retirement over the next decade, the U.S. Air Force and other branches risk losing this invaluable combat aviation experience if they do not provide clear transition pathways.³²

Currently, strict categorization systems across the services force remote pilots to start from scratch through traditional undergraduate pilot training if they wish to transition to manned flight, while simultaneously failing to provide dedicated career tracks for managing advanced autonomous swarms.³² This siloed approach wastes human capital. Leadership must construct transition programs that re-purpose legacy remote pilots into Multi-Domain Warfare Officers or fleet managers for Collaborative Combat Aircraft (CCA) and autonomous swarms.³² These personnel already possess the required tactical acumen, target analysis skills, and intrinsic understanding of networked decision-making; they simply need their technical focus realigned.

7.3 Competency Frameworks for the Fleet Manager

Civilian industry and forward-leaning military schools are already identifying the core competencies required for this new fleet management role. Future training doctrines must heavily deprioritize manual stick-and-rudder skills and elevate the following areas ⁸:

1. Systems Safety and Airspace Management: Operators must understand complex, layered safety management systems (SMS) and dynamic airspace integration, especially crucial during beyond visual line of sight (BVLOS) operations where manual deconfliction is impossible.³¹
2. Cybersecurity and Data Integrity: Recognizing that autonomous swarms are highly vulnerable to electronic warfare, spoofing, and cyber-hijacking. Fleet managers must be trained to secure data streaming from payloads, monitor the integrity of tactical data links, and recognize the signatures of algorithmic manipulation.³¹
3. Macro-Cognitive Adaptability: Operators must be trained in problem-solving and rapid re-allocation of assets when initial plans fail, shifting from focusing on how a drone flies to what the fleet achieves.⁴

8. Re-engineering the Training Ecosystem

To successfully build these new competencies, the military training environment must precisely mirror the intended operational ecosystem. The current model of training, which focuses heavily on sequential checklists and isolated platform operation, is dangerously inadequate for preparing warfighters to manage autonomous swarms.

8.1 Live-Virtual-Constructive (LVC) Environments

The paradigm shift toward fleet management relies heavily on the aggressive expansion of Live-Virtual-Constructive (LVC) training environments.¹² Modern simulators must not just replicate basic flight mechanics or rudimentary targeting; they must simulate high-stress, data-saturated environments where operators practice coordinating logic, allocating roles among diverse AI agents, and maintaining situational awareness under severe electronic warfare and GPS-denied conditions.¹

Furthermore, syllabus iteration must be near-real-time. In mature training ecosystems, instructors work directly with manufacturers to update software and LVC simulations immediately when discrepancies are found in missile behavior or when adversary tactics evolve.¹² The DoD cannot afford training curricula that remain locked into legacy patterns while the software operating the drones is updated weekly.

8.2 Stress Inoculation and Cognitive Fitness

Military training must systematically adopt “stress inoculation training” (SIT). By safely exposing operators to overwhelming data streams, simulated emergencies, and impossible multitasking demands within the simulator, operators build robust neurological pathways.⁴ This deliberate practice teaches operators to regulate their physiological and emotional responses, allowing the prefrontal cortex to maintain executive control during sudden crises, thereby bypassing the amygdala’s freeze response and preventing cognitive tunnel vision.⁴

Additionally, the DoD must invest in cognitive “software” upgrades for the operators themselves. This includes integrating cognitive science-based learning methods to improve long-term memory retention and teaching systematic task simplification and memory cues to boost the effectiveness of short-term working memory.²²

8.3 Fostering Air-Mindedness and Bottom-Up Innovation

As demonstrated in recent conflicts and pilot programs, such as the Marine Corps’ integration of first-person-view (FPV) attack drones, technical and tactical innovations frequently emerge from the bottom up.³⁶ Integrating drone training broadly across Air Force and Marine Corps culture teaches warfighters critical supplementary skills: navigating the complexities of electronic warfare, programming, field maintenance, and even fabricating spare parts using 3D printing.³⁶ By cultivating such broad, cross-disciplinary expertise and fostering adaptive action, the DoD can position its operators to generate transformative effects that enhance strategic impact within the Joint Force, far beyond merely pressing a launch button.

9. Software-Defined Warfare and Acquisition Reform

The transformation of human factors in drone operations is ultimately bounded by the software that connects the human to the machine. The DoD’s primary acquisition challenge is that its current strategies were meticulously designed for an industrial age of hardware procurement, not the digital age of software-defined warfare.³⁸

9.1 Overcoming the Authorization Bottleneck

The rapid, iterative development cycles of AI and autonomous swarm logic are often too fast for rigid defense procurement processes to accommodate. For example, mandatory security vetting processes for cloud technologies, such as FedRAMP, typically impose authorization timelines lasting between 6 and 18 months.³⁸ This serves as a massive bottleneck, preventing the timely deployment of cutting-edge AI tools, adaptive HMIs, and updated machine learning models, creating a substantial, dangerous lag between commercial innovation and military implementation.³⁸

This lag directly degrades operator effectiveness. If operators identify a severe flaw in how an HMI displays swarm telemetry during a deployment, they cannot wait 18 months for a software patch. Current frameworks put the joint force at risk by lacking the agility to address specific AI-related threats, such as adversarial AI designed to deceive U.S. systems, or the rapid proliferation of low-cost, AI-enabled counter-drones.³⁸

9.2 The Transition to Microservices and Continuous Delivery

To enable the fleet manager, the DoD must transition fully to a software-centric, hardware-enabled approach to warfighting.³⁹ This involves abandoning monolithic software applications in favor of microservices architectures. A microservices approach breaks down massive software suites into loosely coupled, independent services that can be altered, updated, patched, or taken offline without affecting the rest of the application or grounding the drone fleet.⁴⁰

The DoD must rapidly implement initiatives like the Collaborative Autonomy Mission Planning and Debrief (CAMP) project, which advances mission planning capabilities, AI model management, and trusted AI governance.³⁵ By leveraging government simulation environments like the Joint Simulation Environment (JSE) and the Joint Digital Autonomy Range (JDAR), the DoD can enable rapid testing, validation, and continuous delivery of autonomy-enabled mission profiles directly to the warfighter’s interface.³⁵ Software requirements must be dynamically managed, and in many cases, exempted from the plodding Joint Capabilities Integration and Development System (JCIDS) process to enable rapid, iterative development that responds directly to operator feedback.³⁹

10. Strategic Recommendations for DoD Leadership

The transition to multi-UAS fleet operations is not simply an upgrade in platform technology; it is a fundamental re-architecting of human-machine symbiosis. To successfully deploy the massive proposed investments in drone swarms and autonomous systems, DoD leadership must aggressively address the systemic human factors currently being overlooked. The following strategic actions are imperative across the DOTMLPF-P (Doctrine, Organization, Training, Materiel, Leadership and Education, Personnel, Facilities, and Policy) spectrum:

1. Mandate Ecological Interface Design (EID) in Procurement: Immediately update all acquisition requirements to ensure future ground control stations and HMIs are built upon EID principles. Interfaces must be inherently capable of supporting M:N (Multiple Operator, Multiple UAS) network architectures. They must abstract raw telemetry into functional health and status data to prevent operator working memory saturation and accommodate the strict neurological limits of visual attention.⁶
2. Integrate and Fund Real-Time Cognitive Monitoring: Fund the integration of real-time physiological monitoring systems—specifically eye-tracking and non-invasive EEG—into operational control stations. Next-generation interfaces must dynamically adjust their visual complexity, alarm frequency, and automation transparency based on the operator’s immediate, measured cognitive load, preventing the onset of the attentional blink and cognitive lockup.⁹
3. Establish a Dedicated “Fleet Manager” Career Track: Formally decouple the operation of highly automated UAS systems from traditional, legacy pilot career tracks. Create a “Multi-Domain Fleet Manager” or equivalent designation, providing rapid transition pathways for experienced MQ-9 and RPA operators. This must allow them to orchestrate autonomous swarms without the redundant requirement of attending traditional undergraduate manned pilot training.³²
4. Implement Rigorous Stress Inoculation Training (SIT): Completely overhaul UAS training pipelines to focus on macro-cognitive adaptability rather than physical flight mechanics. Implement high-fidelity LVC simulations that deliberately induce severe task saturation, communications degradation, and catastrophic system failures to actively train operators out of the startle reflex, building neurological resilience.⁴
5. Accelerate Software-Defined Acquisition Pathways: Exempt critical HMI and swarm logic software development from the rigid, hardware-centric JCIDS processes. Establish dynamic, streamlined requirements that mandate microservices architectures, allowing for continuous, iterative software updates based directly on operator performance data and cognitive feedback gathered from active deployments.³⁸
6. Invest Proportionally in Scalable Sustainment: Formally acknowledge that fielding 300,000 attritable drones requires an immediate, massive, and proportional investment in modular logistics, condition-based maintenance, and highly secure, non-proprietary supply chains. Without a resilient sustainment infrastructure, mass hardware procurement will inevitably collapse under its own logistical weight, neutralizing any tactical advantage.¹³

By designing systems that respect the unyielding neurological limits of the human operator, and by actively cultivating a workforce trained for network oversight rather than manual control, the Department of Defense can move beyond the illusion of hardware superiority and achieve true cognitive dominance in the next generation of warfare.

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Sources Used

1. Pentagon preparing for drone swarm ‘crucible’ | DefenseScoop, accessed April 24, 2026, https://defensescoop.com/2026/03/31/pentagon-preparing-drone-swarm-crucible/
2. War Department Asks Industry to Make More Than 300K Drones, Quickly, Cheaply, accessed April 24, 2026, https://www.war.gov/News/News-Stories/Article/Article/4346822/war-department-asks-industry-to-make-more-than-300k-drones-quickly-cheaply/
3. DOD moves to make its largest-ever investment in drones and anti-drone weapons, accessed April 24, 2026, https://defensescoop.com/2026/04/21/dod-plans-largest-ever-investment-drones-anti-drone-weapons/
4. Cognitive Performance and Decision-Making in Drone Operations – HSToday, accessed April 24, 2026, https://www.hstoday.us/subject-matter-areas/unmanned-vehicles/cognitive-performance-and-decision-making-in-drone-operations/
5. Overloaded Under Stress: Managing Task Saturation and Startle in the Flight Deck, accessed April 24, 2026, https://www.denizkilicgedik.com/post/task-saturation-and-startle-reflex
6. A Cognitive Walkthrough of Multiple Drone Delivery Operations, accessed April 24, 2026, https://ntrs.nasa.gov/api/citations/20210018022/downloads/Cognitive%20Walkthrough%20of%20Multi-Drone%20Delivery%20Ops.Smith%20et%20al.AIAA.2021.pdf
7. Cry in the sky: Psychological impact on drone operators – PMC, accessed April 24, 2026, https://pmc.ncbi.nlm.nih.gov/articles/PMC8611566/
8. Supervising and Controlling Unmanned Systems: A Multi … – Frontiers, accessed April 24, 2026, https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2016.00568/full
9. Understanding Mental Workload in UAV Operators: The Role of Eye-Tracking Technology, accessed April 24, 2026, https://www.cambridge.org/core/blog/2025/04/25/understanding-mental-workload-in-uav-operators-the-role-of-eye-tracking-technology/
10. Navigating the Future of the Drone Industry: Autonomy, AI, and Workforce Transformation – Dronelife, accessed April 24, 2026, https://dronelife.com/2025/09/05/navigating-the-future-of-the-drone-industry-autonomy-ai-and-workforce-transformation/
11. Training for the High-End Fight: The Paradigm Shift for Combat Pilot Training | Defense.info, accessed April 24, 2026, https://defense.info/book/training-for-the-high-end-fight-the-paradigm-shift-for-combat-pilot-training/
12. From Platform to Ecosystem: Training Transformation and the Time …, accessed April 24, 2026, https://defense.info/re-shaping-defense-security/2026/03/from-platform-to-ecosystem-training-transformation-and-the-time-factor/
13. A House of Cards: TiC and the Fragile Foundations of LSCO Sustainment – U.S. Army, accessed April 24, 2026, https://www.army.mil/article/288966/a_house_of_cards_tic_and_the_fragile_foundations_of_lsco_sustainment
14. 300000 Drones: What Hegseth’s Drone Build-Up Means, and What We Still Need to Know, accessed April 24, 2026, https://www.military.com/feature/2025/12/05/300000-drones-what-hegseths-drone-build-means-and-what-we-still-need-know.html
15. Weapon System Sustainment: DOD Identified Critical Cost Growth, and the Army Should Take Action to Yield Cost Savings – GAO, accessed April 24, 2026, https://www.gao.gov/products/gao-26-108140
16. Prefrontal cortex oxygenation during a mentally fatiguing task in normoxia and hypoxia – PMC, accessed April 24, 2026, https://pmc.ncbi.nlm.nih.gov/articles/PMC11208267/
17. Neural Correlates of Workload Transition in Multitasking: An ACT-R Model of Hysteresis Effect – PMC, accessed April 24, 2026, https://pmc.ncbi.nlm.nih.gov/articles/PMC6378922/
18. How humans search for targets through time: A review of data and theory from the attentional blink – PMC, accessed April 24, 2026, https://pmc.ncbi.nlm.nih.gov/articles/PMC2915904/
19. Dynamics of the attentional blink in preverbal infants – PNAS, accessed April 24, 2026, https://www.pnas.org/doi/10.1073/pnas.2526752123
20. Neural correlates of the sense of agency in free and coerced moral decision-making among civilians and military personnel, accessed April 24, 2026, https://dipot.ulb.ac.be/dspace/bitstream/2013/390909/3/bhaf049.pdf
21. Remote Warfare with Intimate Consequences: Psychological Stress in Service Member and Veteran Remotely-Piloted Aircraft (RPA) Personnel, accessed April 24, 2026, https://www.mentalhealthjournal.org/articles/remote-warfare-with-intimate-consequences-psychological-stress-in-service-member-and-veteran-remotely-piloted-aircraft-rpa-personnel.html
22. Cognitive Performance Enhancement for Multi-domain Operations, accessed April 24, 2026, https://press.armywarcollege.edu/cgi/viewcontent.cgi?article=3188&context=parameters
23. Human–Machine Interface Design for Monitoring Safety Risks Associated with Operating Small Unmanned Aircraft Systems in Urban Areas – MDPI, accessed April 24, 2026, https://www.mdpi.com/2226-4310/8/3/71
24. Unmanned System Safety Engineering Precepts Guide for DoD Acquisition – USD(R&E), accessed April 24, 2026, https://www.cto.mil/wp-content/uploads/2023/06/UxS-Precepts-2021.pdf
25. Performance, Trust, and Transparency for Effective Human-Swarm Interaction, accessed April 24, 2026, https://www.researchgate.net/publication/352717120_Performance_Trust_and_Transparency_for_Effective_Human-Swarm_Interaction
26. Improving Human-Machine Collaboration Through Transparency-based Feedback – Part I: Human Trust and Workload Model – Purdue e-Pubs, accessed April 24, 2026, https://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1035&context=mepubs
27. Summary Final Report for Unmanned Aircraft Systems in Air Carrier Operations: UAS Operator Fatigue – Federal Aviation Administration, accessed April 24, 2026, https://www.faa.gov/sites/faa.gov/files/data_research/research/med_humanfacs/oamtechreports/202116.pdf
28. Neuroadaptive changes in brain structural–functional coupling …, accessed April 24, 2026, https://pmc.ncbi.nlm.nih.gov/articles/PMC12329225/
29. EEG-Powered UAV Control via Attention Mechanisms – MDPI, accessed April 24, 2026, https://www.mdpi.com/2076-3417/15/19/10714
30. Drone Fleet Management: Software, Compliance & Scaling Operations, accessed April 24, 2026, https://www.thedroneu.com/blog/drone-fleet-management/
31. Four Must-Have Competencies for Success in Drones | Commercial UAV News, accessed April 24, 2026, https://www.commercialuavnews.com/four-must-have-competencies-for-success-in-drones
32. Keep MQ-9 Pilots Flying – War on the Rocks, accessed April 24, 2026, https://warontherocks.com/keep-mq-9-pilots-flying/
33. Human Factors, Competencies, and System Interaction in Remotely Piloted Aircraft Systems, accessed April 24, 2026, https://www.mdpi.com/2226-4310/13/1/85
34. Beyond Visual Line of Sight (BVLOS) – Federal Aviation Administration, accessed April 24, 2026, https://www.faa.gov/newsroom/beyond-visual-line-sight-bvlos
35. GA-ASI Selected for U.S. Navy Collaborative Autonomy Project | UST, accessed April 24, 2026, https://www.unmannedsystemstechnology.com/2026/04/ga-asi-selected-for-u-s-navy-collaborative-autonomy-project/
36. View of Unifying Air-Mindedness: Every Airman a Drone Pilot, accessed April 24, 2026, https://jcldusafa.org/index.php/jcld/article/view/330/585
37. Marine Corps Launches New Drone Training Program – Department of War, accessed April 24, 2026, https://www.war.gov/News/News-Stories/Article/Article/4369456/marine-corps-launches-new-drone-training-program/
38. The Algorithmic Battlefield: Forging The U.S. Army’s Future Dominance With A New Breed Of Acquisition Leader – USAASC, accessed April 24, 2026, https://asc.army.mil/web/the-algorithmic-battlefield/
39. Commission on Software-Defined Warfare | Atlantic Council, accessed April 24, 2026, https://www.atlanticcouncil.org/wp-content/uploads/2025/03/Commission-on-Software-Defined-Warfare-Final-Report.pdf
40. Software Engineering for Continuous Delivery of Warfighter Capability, accessed April 24, 2026, https://www.cto.mil/wp-content/uploads/2025/08/SWE-Guide-July2025-secured-1.pdf