An Improved Path Planning Algorithm for Mobile Robots

Authors

Haijie Sun, Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China; Key Laboratory of Advanced Equipment Intelligent Manufacturing Technology of Yunnan Province, Kunming 650500, China
Hongjun San, Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China; Key Laboratory of Advanced Equipment Intelligent Manufacturing Technology of Yunnan Province, Kunming 650500, China
Le Xiao, Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China; Key Laboratory of Advanced Equipment Intelligent Manufacturing Technology of Yunnan Province, Kunming 650500, China
Dexin Yao, Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China; Key Laboratory of Advanced Equipment Intelligent Manufacturing Technology of Yunnan Province, Kunming 650500, China
Jiupeng Chen, Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China; Key Laboratory of Advanced Equipment Intelligent Manufacturing Technology of Yunnan Province, Kunming 650500, China
Xiaoyuan Yang, Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China; Key Laboratory of Advanced Equipment Intelligent Manufacturing Technology of Yunnan Province, Kunming 650500, China

Abstract

Abstract: To solve the problems of invalid sampling and non-optimal paths of the RRT, the quasi-stream avoidance algorithm is proposed. The RRT algorithm is introduced to specify the sampling interval to limit the sampling points and enhance the goal-oriented nature of sampling. The quasi-stream avoidance algorithm incorporating the A* algorithm (QSA*) is used to quickly bypass the obstacle when it is encountered. A path optimization algorithm is used to smooth the searched path. The simulation results show that compared with the RRT algorithm, the computation time of the RRT-QSA* algorithm is reduced by 96.83%~99.88%, the number of search nodes is reduced by 86.62%~96.01%, the number of path lengths is reduced by 9.9%~16.7%, and the turning angle decreased by 80.93%~93.04%. The RRTQSA* algorithm shows a more intense improvement in computational efficiency than the RRT algorithm as the map size increases.

Recommended Citation

Sun, Haijie; San, Hongjun; Xiao, Le; Yao, Dexin; Chen, Jiupeng; and Yang, Xiaoyuan (2024) "An Improved Path Planning Algorithm for Mobile Robots," Journal of System Simulation: Vol. 36: Iss. 9, Article 19.
DOI: 10.16182/j.issn1004731x.joss.23-0585
Available at: https://dc-china-simulation.researchcommons.org/journal/vol36/iss9/19

First Page

2193

Last Page

2207

CLC

TP242.6

Recommended Citation

Sun Haijie, San Hongjun, Xiao Le, et al. An Improved Path Planning Algorithm for Mobile Robots[J]. Journal of System Simulation, 2024, 36(9): 2193-2207.

DOI

10.16182/j.issn1004731x.joss.23-0585