General Atomics Aeronautical Systems, Inc. (GA-ASI) announced it successfully integrated and flew the US Air Force Research Laboratory’s (AFRL) Agile Condor Pod on an MQ-9 Remotely Piloted Aircraft (RPA).
The flight test took place at the company’s test and training center in Grand Forks, North Dakota.
The Agile Condor Pod provides on-board high-speed computer processing coupled with machine learning algorithms to detect, correlate, identify, and track targets of interest.
With this capability, the MQ-9 is able to identify objects autonomously utilizing its on-board electro-optical/infrared (EO/IR) sensor and GA-ASI’s Lynx synthetic aperture radar (SAR).
“Computing at the edge has tremendous implications for future unmanned systems,” said GA-ASI President David R. Alexander. “GA-ASI is committed to expanding artificial intelligence capabilities on unmanned systems and the Agile Condor capability is proof positive that we can accurately and effectively shorten the observe, orient, decide and act cycle to achieve information superiority.”
High-powered computing at the edge enables autonomous target detection, identification and nomination at extended ranges and on-board processing reduces communication bandwidth requirements to share target information with other platforms.
As noted by the company, the test is an important step towards greater automation, autonomous target detection, and rapid decision-making. GA-ASI added it would continue to work with AFRL to refine the capability.
