Test units executed the flight in the Eglin Test and Training Complex. The flight builds upon four years of partnership that began with the Skyborg Vanguard and the Autonomous Aircraft Experimentation (AAx) programs.
“The mission proved out a multi-layer safety framework on an AI/ML-flown uncrewed aircraft and demonstrated an AI/ML agent solving a tactically relevant “challenge problem” during airborne operations,” said Col. Tucker Hamilton, chief, AI Test and Operations, for the Department of the Air Force. “This sortie officially enables the ability to develop AI/ML agents that will execute modern air-to-air and air-to-surface skills that are immediately transferrable to other autonomy programs.”
The algorithms were developed by AFRL’s Autonomous Air Combat Operations team. The algorithms matured during millions of hours in high fidelity simulation events, sorties on the X-62 VISTA, Hardware-in-the-Loop events with the XQ-58A, and ground test operations, as depicted in the video at the link below.
“AACO has taken a multi-pronged approach to uncrewed flight testing of machine learning Artificial Intelligence and has met operational experimentation objectives by using a combination of High-performance computing, modeling and simulation, and hardware in the loop testing to train an AI agent to safely fly the XQ-58 uncrewed aircraft,” said AACO Program Manager, Dr. Terry Wilson.
DOD is committed to the responsible employment of AI. To achieve responsible use of AI requires teaming of developers and users of AI enabled autonomy working in collaboration with acquisition specialists.
“AI will be a critical element to future warfighting and the speed at which we’re going to have to understand the operational picture and make decisions,” said Brig. Gen. Scott Cain, AFRL commander. “AI, Autonomous Operations, and Human-Machine Teaming continue to evolve at an unprecedented pace and we need the coordinated efforts of our government, academia, and industry partners to keep pace.”
