2022
DOI: 10.48550/arxiv.2204.13336
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Human Motion Control of Quadrupedal Robots using Deep Reinforcement Learning

Abstract: A motion-based control interface promises flexible robot operations in dangerous environments by combining user intuitions with the robot's motor capabilities. However, designing a motion interface for non-humanoid robots, such as quadrupeds or hexapods, is not straightforward because different dynamics and control strategies govern their movements. We propose a novel motion control system that allows a human user to operate various motor tasks seamlessly on a quadrupedal robot. We first retarget the captured … Show more

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