An Improved A-Star Path Planning Algorithm for Logistics Handling Robots

作者：Jianjun Zhu, Shuai Wang, Longlong Fan · 发表于：2025 IEEE 8th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) · 年份：2025 · DOI：10.1109/auteee67053.2025.11322250

In the context of logistics handling robot applications, this paper proposes an improved A-Star path planning algorithm to address the limitations of the traditional A-Star algorithm, such as long computation time, excessive path length, and unsmooth trajectories, thereby enhancing the operational efficiency of the robot. First, a bidirectional search strategy is adopted, in which the search is simultaneously initiated from both the start and goal points. During node expansion, a dynamic five-neighborhood search strategy and a direct-connection mechanism are introduced. Second, the evaluation function is enhanced by integrating a hybrid dynamic weighting mechanism and a dynamic angle-based heuristic function. Finally, a forward optimization strategy combined with a reverse greedy strategy is employed to optimize the path, and the resulting route is refined by applying a cubic uniform B-spline method. Through multiple simulation experiments, the results demonstrate that the proposed algorithm reduces the average number of search nodes by 74% and the number of turning points by 55.2%; the average path length is shortened by 13.75%, and the average planning time is reduced by 66.5%. These experimental results verify that, compared with the traditional A-Star algorithm, the improved algorithm achieves significantly higher path planning efficiency and demonstrates promising applicability and practical value in logistics handling environments.