Shield AI has successfully flown the BQM-177A target drone autonomously using its Hivemind software, marking a major step toward the US Navy’s first beyond-visual-range autonomy mission on a fast-moving platform.
The test, conducted at Naval Air Station Point Mugu in California, showcased advances in manned-unmanned teaming and highlighted Hivemind’s expanding role across multiple aircraft.
As part of the Experimental Platform for Intelligent Combat project, the demonstration validated seamless control handoff, onboard system communication, and integration with Kratos’ updated Advanced Vehicle Control Laws.
Shield AI led the effort as systems integrator and mission autonomy provider, handling platform modifications, payload integration, and coordination with government and industry partners.
“This milestone reinforces that Shield AI is a highly advanced, low-risk, mission-focused partner capable of rapidly integrating autonomy onto new platforms,” said Christian Gutierrez, Vice President of Hivemind Solutions at Shield AI.
“It reflects our ability to lead complex system integrations while reinforcing our customer’s goals with reliable, scalable, and interoperable autonomy solutions that are ready for real–world operations.”
Strategic Path to Fleet Integration
Originally built as a high-performance aerial target, the BQM-177A served as a low-cost research platform for this test.
US Navy officials consider this role as a way to de-risk autonomy development and inform future Collaborative Combat Aircraft concepts when operational assets are unavailable or too expensive.
To execute the demonstration, Shield AI collaborated with Naval Air Systems Command’s PMA-281 and PMA-208 programs, Kratos, and Coherent Technical Services, Inc.
Kratos provided software updates and integration, while CTSi built the mission planning and control interface within a live-virtual-constructive environment.
The test also advanced adoption of the Pentagon Autonomy Government Reference Architecture, aimed at improving interoperability across autonomous systems.
