Path Planning for Improvement of A* Algorithm and Artificial Potential Field Method

Authors

Xiang Yu, School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaFollow
Chen Jiang, School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaFollow
Sirui Duan, School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
Qianrui Deng, School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Abstract

Abstract: A* algorithm has the problem of too many polyline paths and search nodes, while the artificial potential field (APF) method has the problems of local optimality and unattainability. These problems are investigated in this paper. A new hybrid heuristic function is proposed based on the Euclidean distance and projection distance, based on which the A* algorithm process is improved accordingly. The search nodes of the A* algorithm are reduced, and the search efficiency is improved. The optimal node generated by the new A* algorithm is used as the local target point of the APF algorithm to assist in getting rid of the local optimal point. The potential field function is improved by adding the position relationship between the robot and the target point, and the gain of repulsive force is modified. The generation direction of the repulsive force is optimized. A new algorithm is proposed by fusing the improved two algorithms, and the potential field function of APF method is used to guide the search of the A* algorithm. The improved algorithms are compared in terms of path length, obstacle avoidance effect, and iteration times. The simulation results show that the improved algorithm proposed in this paper has high search efficiency and achieves obstacle avoidance while ensuring the optimal path of the calculation.

Recommended Citation

Yu, Xiang; Jiang, Chen; Duan, Sirui; and Deng, Qianrui (2024) "Path Planning for Improvement of A* Algorithm and Artificial Potential Field Method," Journal of System Simulation: Vol. 36: Iss. 3, Article 21.
DOI: 10.16182/j.issn1004731x.joss.23-0255
Available at: https://dc-china-simulation.researchcommons.org/journal/vol36/iss3/21

First Page

782

Last Page

794

CLC

TP391.9

Recommended Citation

Yu Xiang, Jiang Chen, Duan Sirui, et al. Path Planning for Improvement of A* Algorithm and Artificial Potential Field Method[J]. Journal of System Simulation, 2024, 36(3): 782-794.

Corresponding Author

Jiang Chen

DOI

10.16182/j.issn1004731x.joss.23-0255