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Potential field-based dual heuristic programming for path-following and obstacle avoidance of wheeled mobile robots

Published online by Cambridge University Press:  27 April 2023

Yaoqian Peng ,
Xinglong Zhang Open the ORCID record for Xinglong Zhang [Opens in a new window] ,
Haibin Xie  and
Xin Xu
Yaoqian Peng
Affiliation:
College of Intelligence Science and Technology, National University of Defense Technology, Changsha, 410073, China
Xinglong Zhang*
Affiliation:
College of Intelligence Science and Technology, National University of Defense Technology, Changsha, 410073, China
Haibin Xie*
Affiliation:
College of Intelligence Science and Technology, National University of Defense Technology, Changsha, 410073, China
Xin Xu
Affiliation:
College of Intelligence Science and Technology, National University of Defense Technology, Changsha, 410073, China
*
*Corresponding authors. E-mail: zhangxinglong18@nudt.edu.cn; xhb2575_sx@sina.com
*Corresponding authors. E-mail: zhangxinglong18@nudt.edu.cn; xhb2575_sx@sina.com
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Abstract

Path-following control of wheeled mobile robots has been a crucial research topic in robotic control theory and applications. In path-following control with obstacles, the path-following control and collision avoidance goals might be conflicting, making it challenging to obtain near-optimal solutions for path-following control and obstacle avoidance with low tracking error and input energy consumption. To address this problem, we propose a potential field-based dual heuristic programming (P-DHP) algorithm with an actor–critic (AC) structure for path-following control of mobile robots with obstacle avoidance. In the proposed P-DHP, the path-following control and collision avoidance problems are decoupled into two ones to resolve the control conflict. Firstly, a neural network-based AC is constructed to approximate the near-optimal path-following control policy in a no-obstacle environment. Then, with the trained path-following control policy fixed, a potential field-based control policy structure is constructed by another AC network to generate opposite control forces as the robot moves toward the obstacle, which can guarantee the robot’s control safety and reduce the tracking error and input energy consumption in obstacle avoidance. The simulated and experimental results show that P-DHP can realize near-optimal path-following control with the satisfaction of safety constraints and outperforms state-of-the-art approaches in control performance.

Keywords

dual heuristic programmingwheeled mobile robotspath followingobstacle avoidancepotential field
Type
Research Article
Information
Robotica , Volume 41 , Issue 7 , July 2023 , pp. 1931 - 1946
Copyright
© The Author(s), 2023. Published by Cambridge University Press

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