Path planning design of robots based on improved particle swarm optimization algorithm and artificial potential field method

Lijuan Cai; Jiali Cai; Yuhong Shi

doi:10.1117/12.2652734

20 October 2022 Path planning design of robots based on improved particle swarm optimization algorithm and artificial potential field method

Lijuan Cai, Jiali Cai, Yuhong Shi

Author Affiliations +

Proceedings Volume 12350, 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022); 123501Z (2022) https://doi.org/10.1117/12.2652734
Event: 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022), 2022, Qingdao, China

Abstract

Robot path planning is to find the best path for robot movement considering the interference of surrounding obstacles. In this paper, the feasible region is rasterized and the robot path planning problem is transformed into abstract space that can be dealt with. In order to improve the computational efficiency, the improved particle swarm optimization algorithm combined with artificial potential field method was used to find the best moving path in the grid environment. Bessel curve is used for final smoothing operation to solve the problem of multiple path breaks in grid environment and obtain the final moving path. An example shows that this method can overcome the shortcomings of traditional algorithms and intelligent algorithms in robot path planning, and has strong search and convergence ability.

Citation Download Citation

Lijuan Cai, Jiali Cai, and Yuhong Shi "Path planning design of robots based on improved particle swarm optimization algorithm and artificial potential field method", Proc. SPIE 12350, 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022), 123501Z (20 October 2022); https://doi.org/10.1117/12.2652734

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