Research on autonomous mobile robot path planning based on improved A* algorithm

Jigao Niu; Xiaohui Kou; Chunhua Xu

doi:10.1117/12.3037940

7 August 2024 Research on autonomous mobile robot path planning based on improved A* algorithm

Jigao Niu, Xiaohui Kou, Chunhua Xu

Proceedings Volume 13229, Seventh International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2024); 132291I (2024) https://doi.org/10.1117/12.3037940
Event: Seventh International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2024), 2024, Nanchang, China

Abstract

In order to address the issue of optimal pathfinding in autonomous mobile robot navigation, an improved path planning scheme based on the traditional A* algorithm is proposed. Firstly, aiming at the problem of collision and low planning search efficiency in traditional A* algorithm, a safety distance is set, and the Euclidean distance calculation method is selected in the heuristic function, constructing a cost function with dynamically adjustable heuristic function weights. Secondly, to smooth out the non-smooth paths generated by traditional A* algorithm, a Bezier curve smoothing algorithm is employed for path smoothing. Then, through simulation experiments, the significant improvements of the algorithm in terms of planning efficiency, safety, and path smoothness are verified. Finally, through autonomous navigation experiments, the feasibility of the improved A* algorithm is demonstrated. The research demonstrates that the algorithm designed in this paper can plan the optimal path and safely and efficiently reach the target point.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jigao Niu, Xiaohui Kou, and Chunhua Xu "Research on autonomous mobile robot path planning based on improved A* algorithm", Proc. SPIE 13229, Seventh International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2024), 132291I (7 August 2024); https://doi.org/10.1117/12.3037940

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