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The self-driving car industry has made great autonomy advances, but mostly for well-structured and highly predictable environments. In complex militarily-relevant settings, robotic vehicles have not demonstrated operationally relevant speed and aren’t autonomously reliable. While vehicle platforms that can handle difficult terrain exist, their autonomy algorithms and software often can’t process and respond to changing situations well enough to maintain necessary speeds and keep up with soldiers on a mission.
DARPA’s Robotic Autonomy in Complex Environments with Resiliency (RACER) program aims to make sure algorithms aren’t the limiting part of the system and that autonomous combat vehicles can meet or exceed soldier driving abilities.
RACER will demonstrate game-changing autonomous UGV mobility, focused on speed and resiliency, using a combination of simulation and advanced platforms. It tests algorithms in the field at DARPA-hosted experiments across the country on a variety of terrain. The program provides UGV platforms that research teams can use to develop autonomous software capabilities through repeated cycles of tests on unstructured off-road landscapes. Goals include not only autonomy algorithms, but also creation of simulation-based approaches and environments that will support rapid advancement of self-driving capabilities for future UGVs.
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