AI Algorithms Fly Uncrewed XQ-58A Valkyrie Drone for Three Hour Sortie
Air Force Research Laboratory (AFRL) engineers and researchers used artificial intelligence (AI) agents or algorithms to fly an unmanned XQ-58A Valkyrie aircraft on a three-hour sortie during a July 25 demonstration at Eglin Air Force Base, Florida.
The XQ-58A, developed through an AFRL partnership with Kratos Defense & Security Solutions Inc., is a 30-foot long experimental unmanned aircraft with a range of 3,000 nautical miles designed to act as a "loyal wingman" while controlled and flying in tandem with a manned aircraft. With an operational ceiling of 50,000 feet and a top speed exceeding .9 Mach, Kratos built the aircraft for AFRL's Low-Cost Attritable Aircraft Technology (LCAAT) project portfolio, established to "break the escalating cost trajectory of tactically relevant aircraft and provide an unmanned escort or wingman aircraft alongside a crewed fighter aircraft in combat," according to Kratos.
During the three-hour sortie in July, AFRL used the same AI algorithms that previously demonstrated their ability to pilot the Lockheed Martin-built X-62A during a flight evaluation program held at Edwards Air Force Base in December 2022. The algorithms were developed by AFRL’s Autonomous Air Combat Operations (AACO) team and have 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.
“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 flight builds upon four years of partnership that began with the Skyborg Vanguard and the Autonomous Aircraft Experimentation (AAx) programs.
“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.
Top Stories
INSIDERManned Systems
Are Boeing 737 Rudder Control Systems at Risk of Malfunctioning?
Technology ReportPropulsion
Off-Highway Hybrids Are Entering Prime Time
INSIDERRegulations/Standards
Is the Department of Defense Stockpiling Enough Critical Materials?
INSIDERSensors/Data Acquisition
Designing Next-Generation Carbon Dioxide Removal Technology for Better Life in...
INSIDERRF & Microwave Electronics
Barracuda: Anduril's New Software-Defined Autonomous Air Vehicles
NewsEnergy
Webcasts
Aerospace
The Benefits and Challenges of Enabling Direct-RF Sampling
Test & Measurement
The Testing Equipment You Need to Keep Pace with Evolving EV...
Automotive
Advances in Zinc Die Casting Driving Quality, Performance, and...
Automotive
Fueling the Future: Hydrogen Solutions for Commercial Vehicle...
Aerospace
Maximize Asset Availability in the Aerospace and Defense Industry
Aerospace
Similar Stories
Application BriefsUnmanned Systems
AI Algorithms Fly Valkyrie XQ-58A
INSIDERUnmanned Systems
Airbus Achieves Autonomous In-Flight Control of Drone From Tanker
INSIDERRF & Microwave Electronics
AI Pilots X-62A in First Aerial Dogfight
INSIDERSoftware
Method Measures a Drone’s Ability to Recover
INSIDERAR/AI
Chevron Waiver Unlocks New Era for BVLOS Commercial Drone Operations in US
INSIDERData Acquisition
DARPA AI Algorithms Transition from Simulator to Flying Modified F-16