Research on path planning in complex environment based on improved A* algorithm
KANG Kaishen
HUANG Hailong
Abstract：[Objective]The global path planning algorithm for mobile robots currently faces challenges such as excessive inflection points,prolonged computation time,and inefficiency in complex environments.To address these issues,an improved A* algorithm was proposed and experimentally validated under complex environmental conditions.[Methods]Firstly,the traditional 8-neighborhood search of the A* algorithm was expanded to a 12-neighborhood search.Subsequently,based on the collision model derived from environmental heuristic information processing,the searched paths were categorized into four cost types,with the least-cost path selected as the optimal trajectory for the mobile robot.Finally,the optimal path obtained from the planning was smoothed using the cubic spline interpolation method.[Results]Test results demonstrate that,compared to the traditional A* algorithm,the improved A* algorithm achieves search speed improvements of 32.68%,33.40%and 20.17%in simple,moderate and complex environments,respectively.Additionally,the number of severe path deflections is reduced by 35.71%,43.67%and 47.58%in these environments.The obtained path has the advantages of fewer nodes,a shorter distance,and a smoother trajectory.
Keywords：Mobile robotGlobal path planningA* algorithmCost pathCubic spline interpolation method
Publication Date：2025-07-31
Online Publishing Date：2026-09-12(First online date of this platform, not the publication date of the document)
Pages：9( 22-30 )