L3Harris Technologies and Shield AI have jointly demonstrated a fully autonomous system designed to detect, track, and neutralize unmanned aerial threats in contested environments. The demonstration showcased the integration of Shield AI’s Hivemind artificial intelligence software with L3Harris’ V-BAT unmanned aerial system (UAS), offering a resilient solution for counter-drone operations without reliance on GPS or communications links.
Autonomous Counter-UAS Capability Without GPS or Comms
The joint demonstration took place at the Army’s Yuma Proving Ground in Arizona in September 2025. It featured multiple V-BATs equipped with Shield AI’s Hivemind software operating autonomously in a simulated adversarial drone engagement scenario. The key achievement was the execution of coordinated search-and-detect missions against enemy drones without any human input or external communication infrastructure.
Hivemind enables aircraft to perform complex tasks such as dynamic obstacle avoidance, target acquisition, and threat engagement autonomously. It is designed specifically for denied environments where GPS jamming or loss of comms would otherwise cripple traditional UAS operations. This capability aligns with the Department of Defense’s push for resilient autonomous systems capable of operating in electronic warfare-contested theaters.
V-BAT UAS as a Multi-Mission Platform
The V-BAT is a Group 3 vertical takeoff and landing (VTOL) unmanned aerial system developed by Martin UAV (acquired by Shield AI) and now produced in partnership with L3Harris. It has become one of the most versatile tactical drones in its class due to its tail-sitter design that enables launch and recovery from confined spaces such as ship decks or urban rooftops.
Key specifications of the latest V-BAT iteration include:
- Endurance: Up to 11 hours
- Range: >100 km datalink range
- Payload capacity: ~11 kg modular payload bay
- Sensor options: EO/IR gimbals, SIGINT packages, radar modules
- MTOW (Maximum Takeoff Weight): ~56 kg
The platform has been fielded by multiple U.S. services including SOCOM and the Navy under various programs such as Mi2CE (Multi-INT Multi-Mission Tactical UAS). Its modularity allows rapid integration of new payloads like electronic warfare pods or loitering munition dispensers.
Shield AI’s Hivemind: Swarm Autonomy at Scale
At the core of this demonstration is Shield AI’s proprietary Hivemind software stack — an onboard autonomy solution that allows aircraft to operate independently without human pilots or remote operators. Unlike traditional autopilots that follow pre-programmed waypoints, Hivemind uses reinforcement learning-based neural networks trained in simulation environments to make real-time decisions based on sensor inputs.
This architecture supports multi-agent coordination across swarms of aircraft. In this test event, multiple V-BATs collaborated autonomously to patrol an area of interest, identify hostile drones via onboard sensors, share threat data locally via mesh networking protocols (when available), and engage targets using pre-defined tactics — all without centralized control.
The system reportedly demonstrated successful detection and tracking of fast-moving drone targets simulating Group I/II threats — typical quadcopters or fixed-wing drones used in asymmetric attacks. While no kinetic interceptors were used during this trial phase, future iterations may integrate effectors such as EW jammers or interceptor drones equipped with net guns or directed energy weapons.
Tactical Implications for Future Drone Warfare
This capability addresses one of the most pressing operational gaps facing modern militaries — scalable defense against low-cost drone swarms operating below radar coverage thresholds. Traditional counter-UAS systems rely heavily on centralized command structures and high-bandwidth data links vulnerable to jamming or spoofing.
An autonomous mesh-networked solution like V-BAT + Hivemind offers several advantages:
- No reliance on GPS signals — crucial for EW-contested zones
- No need for persistent SATCOM or radio comms during mission execution
- Rapid deployment from austere locations without infrastructure setup
- Scalable swarm behavior enabling wide-area coverage with minimal operator burden
- Potential integration with kinetic/non-kinetic effectors for layered defense
Program Status and Future Development Pathways
This demonstration builds upon previous collaborative efforts between L3Harris and Shield AI under various DoD innovation initiatives including AFWERX SBIR contracts and SOCOM technology accelerators. The companies are positioning their joint solution as a candidate for upcoming procurement programs focused on expeditionary counter-drone capabilities.
L3Harris recently announced plans to expand production capacity for Group III UAS platforms at its facility in Tulsa, Oklahoma — potentially signaling anticipation of scaled demand from military customers. Meanwhile, Shield AI continues development on larger-scale autonomy projects including teaming manned fighters with swarms under DARPA’s ACE program.
Conclusion: Toward Autonomous Air Superiority at Tactical Edge
The successful demonstration marks a significant milestone toward achieving fully autonomous air superiority against emerging unmanned threats. As adversaries increasingly deploy cheap commercial drones en masse for ISR or kamikaze strikes — particularly evident in conflicts like Ukraine — Western militaries are racing to field countermeasures that are both effective and survivable under electronic attack conditions.
L3Harris’ ruggedized VTOL platform combined with Shield AI’s combat-tested autonomy stack presents a compelling option for forward-deployed units seeking plug-and-play counter-UAS solutions untethered from fragile communications networks. Further testing involving live-fire interceptors will be critical before operational deployment decisions are made by acquisition authorities.
