A Robot Motion Planning Algorithm in the Human Robot Coexisting Environment

Wenzheng Chi1, Max Q.-H. Meng1

  • 1The Chinese University of Hong Kong

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Abstract

In the human robot coexisting environment, to reach the target place efficiently and safely is very meaningful for the mobile service robot. In this paper, a Risk-based Dual Tree Rapidly exploring Random Tree (Risk-DTRRT) algorithm is proposed for robot motion planning in the human robot coexisting environment. The experimental results in both simulations and real world experiments have confirmed that the proposed algorithm can deliver satisfying performance in the dynamic environment.

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