动态环境下基于自适应步长Informed-RRT*和人工势场法的机器人混合路径规划

doi:10.3969/j.issn.1000-1158.2023.01.05

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Abstract In order to solve the path planning problem of mobile robot in the dynamic environment, a hybird strategy based on the global and local algorithms is proposed by combining the Informed RRT* and artificial potential field method. Firstly, the target offset method and adaptive step size method are designed in the process of informed RRT* random point selection to reduce the redundant search and unnecessary tree growth. Corridor optimization and time redistribution method are introduced to optimize the nodes of path for making the path more smooth.Secondly, the artificial potential field method based on subtarget points is employed for the local path planning, and the problem of easy to fall into local minimum and unreachable near the target point for the artificial potential field method is solved. The sub target point is set to make sure that the mobile robot can escape the local minimum and complete the mission. The simulation results show that the time to find a path in a static environment was 71.98% shorter by using adaptive step-length Informed-RRT* algorithm compared to the Informed-RRT* algorithm. Compared to the artificial potential field method,the search time and the path length are decreased 15.4% and 11.1%, respectively, by using the bybird algorithm.

Key words： metrology mobile robot motion planning adaptive step size Informed-RRT* artificial potential field

Received: 15 October 2021 Published: 13 January 2023

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TB92

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	ZHENG Wei
	WANG Hao
	WANG Hong-bin

Cite this article:

ZHENG Wei,WANG Hao,WANG Hong-bin. Adaptive Step Size Informed-RRT* and Artificial Potential Field Algorithm for Hybrid Path Planning of Robot[J]. Acta Metrologica Sinica, 2023, 44(1): 26-34.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2023.01.05 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2023/V44/I1/26

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