DARPA wants autonomous vehicles that drive as well as humans
The Defense Advanced Research Projects Agency is looking to boost the performance of algorithms to bring the driving performance of unmanned ground vehicles (UGV) on par with human-piloted vehicles.
The Robotic Autonomy in Complex Environments with Resiliency (RACER) program aims to leverage autonomy algorithms to help unmanned vehicles maneuver in unstructured off-road terrain at speed, limited only by vehicle mechanical limits, safety and sensor limitations, rather than by software or processing time.
“RACER will demonstrate game-changing autonomous ground combat vehicle mobility using a combination of simulation and advanced platforms,” DARPA said in its proposers day announcement. So performers can focus on developing algorithms DARPA plans to provide the UGV platforms, including sensors, computing resources and a baseline autonomy stack, as government-furnished equipment.
The Army Reseach Lab has also been focusing on algorithms to advance UGVs. Researchers from ARL and the University of Texas at Austin are working on a suite of algorithms, libraries and software components that intelligent systems can use for navigation, planning, perception, control and reasoning when performing specific tasks. The goal is to teach ground robots to learn by doing, rather than responding to verbal commands, which will improve how autonomous systems move through rugged and unfamiliar terrain.
ARL’s Scalable, Adaptive and Resilient Autonomy program is looking to improve how autonomous ground systems travel through increasingly complex off-road environments. Software developed by participants will be integrated into testbed platforms and ARL’s autonomous systems software repository so it will be more broadly available.
DARPA plans to release a broad agency announcement for RACER in October, and a virtual proposers day will be held Oct. 9, 2020 via Zoom.gov.
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