CONNECTING THE DEFENCE COMMUNITY WITH INSIGHT, INTELLIGENCE & OPPORTUNITIES

Officially Supported By:   Supply2Defence

Official Media Partners for:

General Atomics Aeronautical Systems, Inc.(GA-ASI), with the support of SRC Inc., has successfully integrated and flew the Air Force Research Laboratory’s (AFRL) Agile Condor Pod on an MQ-9 Remotely Piloted Aircraft (RPA) at GA-ASI’s Flight 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 utilising its on-board Electro-optical/Infrared (EO/IR) sensor and GA-ASI’s Lynx Synthetic Aperture Radar (SAR).

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. This is an important step towards greater automation, autonomous target detection, and rapid decision-making. GA-ASI will continue to work with AFRL to refine the capability and foster its transition to operational constructs that will improve warfighters’ ability to operate in contested or denied environments.

GA-ASI President David R. Alexander, said: “Computing at the edge has tremendous implications for future unmanned systems. 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. GA-ASI is excited to continue working with AFRL to advance artificial intelligence technologies that will lead to increased autonomous mission capabilities.”

image courtesy of GA-ASI

If you would like to join our community and read more articles like this then please click here.

ai artificial intelligence GA-ASI

Post written by: Matt Brown

RELATED ARTICLES

The whitepaper has discovered that harnessing technology such as AI and drones to bypass issues around landmine pattern detection can make threat identification faster and more accurate

February 19, 2025

Land - UK-Ukraine TechExchange identifies recommendations to improve efficiency within landmine clearing

A new whitepaper from UK-Ukraine TechExchange, a collaborative forum around the key issues affecting the war in Ukraine and its future

The £16M investment will fund Centres for Doctoral Training (CDT) led from the universities of Southampton and Edinburgh, forging closer links between defence and academia.

January 20, 2025

Why AI must support not supplant human decision-making in defence

There is a fundamental difference between human and machine intelligence. But, increasingly, organisations look at artificial intelligence (AI) as an