Path Planning Algorithm for Logistics Robots Based on Improved A*

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.

Authors

Publication Details

Journal
Artificial Intelligence and Robotics Research
Published
2025-01-01
DOI
https://doi.org/10.12677/airr.2025.143064
Citations
1
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
1.28
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article

Path Planning Algorithm for Logistics Robots Based on Improved A*

宽 徐
1 citations
Artificial Intelligence and Robotics Research
Robotic Path Planning Algorithms
1.28
article

Path Planning Algorithm for Logistics Robots Based on Improved A*

宽 徐
article en
1 citations

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.

Artificial Intelligence and Robotics ResearchVol. 14(03)
Openalex Percentile: Top 20%
Robotic Path Planning Algorithms
1.28
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Path Planning Algorithm for Logistics Robots Based on Improved A* — 宽 徐 · Artificial Intelligence and Robotics Research (2025) | TGRS Research Map | TGRS