Path planning for mobile robots based on improving Dijkstra algorithm

Qiaoling Ma; Ruiqi Yang; Tianjiao Lian; Gan Wang; Son Mu

doi:10.1117/12.2678830

25 May 2023 Path planning for mobile robots based on improving Dijkstra algorithm

Qiaoling Ma, Ruiqi Yang, Tianjiao Lian, Gan Wang, Son Mu

Proceedings Volume 12712, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2023); 127121F (2023) https://doi.org/10.1117/12.2678830
Event: International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2023), 2023, Huzhou, China

Abstract

In response to the traditional Dijkstra algorithm, the long search time of pheromone and the occasional redundant inflection points When the final path is obtained can lead to the inefficiency of the algorithm due to its many traversed nodes. Therefore, this paper proposes the use of pheromone calculation method to improve Dijkstra's algorithm. The experimental results show that the optimized algorithm can largely reduce the inflection points generated during path planning and reduce the movement cost of the mobile robot path finding.

Citation Download Citation

Qiaoling Ma, Ruiqi Yang, Tianjiao Lian, Gan Wang, and Son Mu "Path planning for mobile robots based on improving Dijkstra algorithm", Proc. SPIE 12712, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2023), 127121F (25 May 2023); https://doi.org/10.1117/12.2678830

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