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Residual Policy Learning Facilitates Efficient Model-Free Autonomous Racing

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1 Published in 2022 at "IEEE Robotics and Automation Letters"

DOI: 10.1109/lra.2022.3192770

Abstract: Motion planning for autonomous racing is a challenging task due to the safety requirement while driving aggressively. Most previous solutions utilize the prior information or depend on complex dynamics modeling. Classical model-free reinforcement learning methods… read more here.

Keywords: policy learning; learning facilitates; autonomous racing; residual policy ... See more keywords