Year: 2025
Type: article
Abstract: 针对物流机器人路径规划中使用的传统A*搜索算法存在的搜索时间长、效率低等问题，本文提出了一种改进的A*搜索算法。该算法引入动态目标重定向方法解决双向A*搜索算法搜索区域不重合问题，根据障碍物信息和搜索方向动态调整搜索范围，将全局八邻域修改为动态n邻域，有效提高了搜索效率。实验结果表明，改进算法在随机地图中的平均搜索区域减少60.64%，平均搜索时间缩短28.88%；在模拟物流仓库地图中，平均搜索区域减少59.96%，平均搜索时间缩短40.50%，该算法可以有效提高移动物流机器人的路径规划效率。Aiming at the problems of long search time and low efficiency of the traditional A* search algorithm used in the path planning of logistics robots, this paper proposes an improved A* search algorithm. The algorithm introduces a dynamic target redirection method to solve the problem that the search area of the bidirectional A* search algorithm is not coincident. According to the obstacle information and the search direction, the search range is dynamically adjusted, and the global eight neighborhood is modified into a dynamic n neighborhood, which effectively improves the search efficiency. The experimental results show that the average search area of the improved algorithm in random maps is reduced by 60.64%, and the average search time is reduced by 28.88%; in the simulated logistics warehouse map, the average search area is reduced by 59.96%, and the average search time is reduced by 40.50%. This algorithm can effectively improve the path-planning efficiency of mobile logistics robots.
Author: 宽 徐
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4410838148