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Obstacle avoidance path planning of 6-DOF robotic arm based on improved A* algorithm and artificial potential field method

Published online by Cambridge University Press:  29 November 2023

Xianxing Tang Open the ORCID record for Xianxing Tang [Opens in a new window] ,
Haibo Zhou  and
Tianying Xu
Xianxing Tang
Affiliation:
School of Mechanical and Electrical Engineering, Central South University, Changsha, Hunan, China State Key Laboratory of High Performance Complex Manufacturing, Central South University, Changsha, Hunan, China
Haibo Zhou*
Affiliation:
School of Mechanical and Electrical Engineering, Central South University, Changsha, Hunan, China State Key Laboratory of High Performance Complex Manufacturing, Central South University, Changsha, Hunan, China
Tianying Xu
Affiliation:
School of Mechanical and Electrical Engineering, Central South University, Changsha, Hunan, China State Key Laboratory of High Performance Complex Manufacturing, Central South University, Changsha, Hunan, China
*
Corresponding author: Haibo Zhou; Email: zhouhaibo@csu.edu.cn
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Abstract

Most studies on path planning of robotic arm focus on obstacle avoidance at the end position of robotic arm, while ignoring the obstacle avoidance of robotic arm joint linkage, and the obstacle avoidance method has low flexibility and adaptability. This paper proposes a path obstacle avoidance algorithm for the overall 6-DOF robotic arm that is based on the improved A* algorithm and the artificial potential field method. In the first place, an improved A* algorithm is proposed to address the deficiencies of the conventional A* algorithm, such as a large number of search nodes and low computational efficiency, in robotic arm end path planning. The enhanced A* algorithm proposes a new node search strategy and local path optimization method, which significantly reduces the number of search nodes and enhances search efficiency. To achieve the manipulator joint rod avoiding obstacles, a method of robotic arm posture adjustment based on the artificial potential field method is proposed. The efficiency and environmental adaptability of the robotic arm path planning algorithm proposed in this paper are validated through three types of simulation analysis conducted in different environments. Finally, the AUBO-i10 robotic arm is used to conduct path avoidance tests. Experimental results demonstrate that the proposed method can make the manipulator move smoothly and effectively plan an obstacle-free path, proving the method’s viability.

Keywords

6-DOF robotic armobstacle avoidancepath optimizationartificial potential field method
Type
Research Article
Information
Robotica , Volume 42 , Issue 2 , February 2024 , pp. 457 - 481
Copyright
© Central South University, 2023. Published by Cambridge University Press

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