Obstacle Avoidence Path Planning for Robot Arm Based on Mixed Algorithm of Artificial Potential Field Method and RRT

doi:10.3969/j.issn.1007-7375.e17-2002

Abstract

Abstract: To solve the problem of artificial potential field algorithm being liable to fall into local minimum in the obstacle avoidance path planning of industrial robot arm, a combination of artificial potential field and improved Rapidly-exploring Random Tree (RRT) algorithm is applied. Firstly, artificial potential field algorithm is used in local obstacle avoidance path planning. When falling into local minimum, the improved RRT algorithm can adaptively select the temporary target point and make the search process jump out of the local minimum point. In addition, artificial potential field algorithm will be applied when the robot arm leaves the local minimum. This method not only achieves obstacle avoidance on the end effector of the robot arm, but also prevents the collision between the rod and the obstacle, eventually bringing the end effector to the target point. The simulation experiments show that the proposed method is simple and can adapt to the change of environment and is still effective in complex environment.The algorithm can satisfy the requirement of the obstacle avoidance of the robot arm. Finally, the experimental results show the consistency between the actual and the simulation results.

Key words: artificial potential field method, rapidly-exploring random tree, industrial robot arm, obstacle avoidance, path planning

CLC Number:

TP241.2

HE Zhaochu, HE Yuanlie, ZENG Bi. Obstacle Avoidence Path Planning for Robot Arm Based on Mixed Algorithm of Artificial Potential Field Method and RRT[J]. Industrial Engineering Journal , 2017, 20(2): 56-63.

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