Research on global path planning for automated guided vehicles based on bidirectional A* algorithm
SU Muxiong
YE Shulin
Abstract：In traditional A* algorithm-based global path planning for larger environments,issues such as an excessive number of search nodes,lengthy algorithm execution times,and convoluted paths arise.To address these challenges,an improved bidirectional A* algorithm is introduced in this study.This approach incorporates the concept of artificial potential fields to provide a sense of direction in the search process.Additionally,a turning cost is integrated to promote smoother paths,while obstacle factors are introduced to favor the selection of broader path expansions.Finally,eight simulation runs are conducted to compare the proposed improved A*algorithm with traditional A* and bidirectional A* algorithms,as well as an enhanced algorithm without obstacle factors.Evaluation metrics including path length,time,node count,and number of turns are utilized for comparison.The simulation results demonstrate that the improved A* algorithm reduces the number of search nodes by 75.9%compared to the bidirectional A* algorithm,decreases the number of turns by 53.6%,and accelerates runtime by 84.1%.
Keywords：path planningbidirectional A* algorithmgravitational conceptturning costobstacle factor
Publication Date：2024-05-30
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 20-26 )