Improvement of A* Algorithm in Path Planning of Mobile Robot

Authors

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
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
Yaru Wang, Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China
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
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 excessively redundant nodes, low search efficiency, and excessive path turning angle in the path search of the traditional A* algorithm, an improved A* algorithm is proposed to plan the optimal path. First, the amount of search neighborhood of the A* algorithm is increased to 24 to obtain a more accurate and comprehensive search field. Second, the angle search algorithm is introduced, eliminating the unnecessary nodes in the path search and making the search more target-oriented. Third, the heuristic function is weighted by the exponential attenuation through the relative position of the current point and the target point, to deal with the relationship between the search speed and the path length. Finally, the obtained path is smoothed to reduce the number of path bends and the bending angle, making the robot move more smoothly. The results show that, compared with the search speed of the original A* algorithm, that of the improved one is increased by 29.16% ~ 65.82% in a complex environment and by 41.87% ~ 64.71% in a simple environment, and the number of path bends is reduced by 27.27% ~ 63.64% and 59.09% ~ 62.12%. Compared to the D* algorithm, there are significant improvements in pathfinding speed, traversing nodes, and the number of path bends. Furthermore, experiments on the improved A* algorithm are conducted in the real environment to verify its better performance and path planning ability.

Recommended Citation

Yao, Dexin; San, Hongjun; Wang, Yaru; Sun, Haijie; Chen, Jiupeng; and Yang, Xiaoyuan (2024) "Improvement of A* Algorithm in Path Planning of Mobile Robot," Journal of System Simulation: Vol. 36: Iss. 11, Article 16.
DOI: 10.16182/j.issn1004731x.joss.23-0968
Available at: https://dc-china-simulation.researchcommons.org/journal/vol36/iss11/16

First Page

2684

Last Page

2698

CLC

TP391.9

Recommended Citation

Yao Dexin, San Hongjun, Wang Yaru, et al. Improvement of A* Algorithm in Path Planning of Mobile Robot[J]. Journal of System Simulation, 2024, 36(11): 2684-2698.

Corresponding Author

San Hongjun

DOI

10.16182/j.issn1004731x.joss.23-0968