Defense Advanced Research Projects AgencyTagged Content List

Air Systems

Manned and unmanned aerial systems, including fixed-wing and rotary-wing aircraft and supporting technologies

Showing 9 results for Air + Algorithms RSS
DARPA’s AlphaDogfight Trials Final event, originally scheduled for April, has been rescheduled for the summer due to the COVID-19 pandemic. The third and final trial is now planned for Aug. 17-20, 2020, at AFWERX, the Air Force’s innovation hub, in Las Vegas, Nevada.
March 26, 2020,
DARPA will host a Proposers Day in support of recently announced BAA HR001120S0028, Air Combat Evolution (ACE) Technical Area 1 (TA-1) on March 26, 2020, via webinar from 8:00 AM to 12:00 PM, Eastern Time (ET). The purpose of this Proposers Day is to provide information on TA-1 of the ACE program; promote additional discussion on this topic; address questions from potential proposers; and provide a forum for potential proposers to interact with potential teaming partners.
May 17, 2019 ,
DARPA Conference Center
The Strategic Technology Office is holding a Proposers Day meeting to provide information to potential proposers on the objectives of the new Air Combat Evolution (ACE) program and to facilitate teaming. The goal of ACE is to automate air-to-air combat, enabling reaction times at machine speeds and freeing pilots to concentrate on the larger air battle. Turning aerial dogfighting over to AI is less about dogfighting, which should be rare in the future, and more about giving pilots the confidence that AI and automation can handle a high-end fight.
In a target-dense environment, the adversary has the advantage of using sophisticated decoys and background traffic to degrade the effectiveness of existing automatic target recognition (ATR) solutions. Airborne strike operations against relocatable targets require that pilots fly close enough to obtain confirmatory visual identification before weapon release, putting the manned platform at extreme risk. Radar provides a means for imaging ground targets at safer and far greater standoff distances; but the false-alarm rate of both human and machine-based radar image recognition is unacceptably high. Existing ATR algorithms also require impractically large computing resources for airborne applications.