General Atomics reported successful tests during the autonomous flight of the Avenger MQ-20A drone equipped with artificial intelligence.

This was reported in the press service of the company. During testing, the drone was flying autonomously for 30 minutes.

The flight made use of GA-ASI’s novel Reinforcement Learning (RL) architecture to develop and validate an RL agent in an operationally relevant environment.

The team flew “chase and avoid behavior” where real-time updates were made to the flight path in order to avoid adversaries.

Live tracks were provided to the system using the Infrared Search and Track (IRST) sensor network that was supplied by Lockheed Martin.

“The flight was a tremendous success and demonstrated a number of groundbreaking capabilities in the race to operationalize autonomy for Collaborative Combat Aircraft (CCA). It’s exciting to see how AI can be used to advance how and where we fly unmanned systems as the complexity of the battlespace increases. Our ‘chase and avoid’ agent’s ability to dynamically update the flight path as threats were identified is the first step towards building an ecosystem of collaborative autonomous combat aircraft,” said GA-ASI Senior Director of Advanced Programs Michael Atwood.

This flight was another one in an ongoing series of autonomous flights performed by GA-ASI using internal research and development funding to prove important AI/ML concepts for advanced UAS.

Avenger is a long-endurance, medium-to-high-altitude Remotely Piloted Aircraft (RPA) system. The drone can perform wide-area surveillance, and time-sensitive strike missions over land or sea.

Unlike the previous MQ-1 Predator and MQ-9 Reaper (Predator B) drones, the Avenger is equipped with a turbofan engine. Its design also includes stealth features – internal weapon storage and an S-shaped exhaust to reduce infrared and radar signatures.