Deep Reinforcement Learning With Optimized Reward Functions for Robotic Trajectory Planning
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DOI: 10.1109/access.2019.2932257
Abstract: To improve the efficiency of deep reinforcement learning (DRL)-based methods for robotic trajectory planning in the unstructured working environment with obstacles. Different from the traditional sparse reward function, this paper presents two brand-new dense reward… read more here.
Keywords: reward functions; reinforcement learning; trajectory; deep reinforcement ... See more keywords