机械与电子2026，Vol.44Issue(3)：55-60,6.
基于自适应多邻域A*算法的AGV路径规划优化与平滑
Optimization and Smoothing of AGV Path Planning Based on Adaptive Multi-neighborhood A* Algorithm
摘要
Abstract
To address the issues of slow search speed,redundant nodes,and non-smooth paths in tra-ditional A* algorithm for Automated Guided Vehicle(AGV)path planning,an improved method integra-ting adaptive multi-neighborhood search and B-spline curves is proposed.Firstly,the neighborhood ex-pansion mode is dynamically selected based on the obstacle density,and the heuristic function is dynamical-ly adjusted to enhance search efficiency and path quality.Subsequently,B-spline curves are utilized to smooth the generated path,ensuring curvature continuity to meet the kinematic constraints of the chassis.Experimental results show that compared to the traditional 8-neighborhood A* algorithm,the proposed method reduces the path length by approximately 16%,decreases the number of expanded nodes by about 85%,shortens the computation time by around 15%,and reduces the number of turns and the maximum curvature by approximately 66.70%and 62.40%respectively.These improvements significantly enhance the smoothness,executability,and planning efficiency of AGV path.关键词
AGV/自适应/A*算法/B样条曲线/路径平滑Key words
AGV/adaptive/A* algorithm/B-spline curve/path smoothing分类
信息技术与安全科学引用本文复制引用
黄立标,庄嘉颖,陈宇轩,张淑慧,黄瑞金,王福杰,樊开夫..基于自适应多邻域A*算法的AGV路径规划优化与平滑[J].机械与电子,2026,44(3):55-60,6.基金项目
国家自然科学基金资助项目(62203116) （62203116）
广东省教育厅普通高校重点科研平台和项目(2025ZDZX3037) （2025ZDZX3037）
广东省科协青年科技人才培育计划项目(SKXRC2025441) （SKXRC2025441）
