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融合改进A*与DWA算法的机器人路径规划

谢德瀚 高金凤 贾国强 李乐宝 苏雯 梅从立

电子科技2026,Vol.39Issue(1):64-72,96,10.
电子科技2026,Vol.39Issue(1):64-72,96,10.DOI:10.16180/j.cnki.issn1007-7820.2026.01.009

融合改进A*与DWA算法的机器人路径规划

Integration of Improved A* and DWA Algorithms for Robot Path Planning

谢德瀚 1高金凤 1贾国强 2李乐宝 1苏雯 1梅从立3

作者信息

  • 1. 浙江理工大学信息科学与工程学院,浙江 杭州 310018
  • 2. 浙江孚宝智能科技有限公司,浙江 杭州 311103
  • 3. 浙江水利水电学院电气工程学院,浙江 杭州 310048
  • 折叠

摘要

Abstract

In view of the problems of redundant expansion of nodes in the traditional A* algorithm,the path be-ing close to obstacles,as well as the trajectory oscillation and easy falling into local minima in the traditional DWA(Dynamic Window Approaches)algorithm,this study proposes a robot path planning method that integrates and im-proves the A* and DWA algorithms.The cost function of the traditional A* algorithm is improved to remove redundant expanded nodes.The selection strategy of child nodes is improved to avoid the path being close to obstacles,and un-necessary turning points are removed through bidirectional smoothness optimization.An adaptive distance factor is intro-duced into the evaluation function of the DWA algorithm to reduce the oscillation of the trajectory,and the discrete nodes of the prior path of the A*algorithm are taken as the local target points of the DWA algorithm for algorithm inte-gration.The simulation experiments show that the number of expanded nodes of the improved A* algorithm is reduced by 118,the planning time is reduced by 29.9%,and the planning speed of the improved DWA algorithm is increased by 5.3%.The proposed integrated algorithm can ensure the global optimality of the path,avoid falling into local mini-ma,and achieve real-time obstacle avoidance for unknown obstacles.

关键词

机器人/路径规划/A*算法/DWA算法/启发函数/子节点选取/双向平滑度优化/距离因子

Key words

robot/path planning/A* algorithm/DWA algorithm/heuristic function/selection of child nodes/bidi-rectional smoothness optimization/distance factor

分类

信息技术与安全科学

引用本文复制引用

谢德瀚,高金凤,贾国强,李乐宝,苏雯,梅从立..融合改进A*与DWA算法的机器人路径规划[J].电子科技,2026,39(1):64-72,96,10.

基金项目

国家自然科学基金(62073296 ()

62006209) ()

浙江省自然科学基金(LQ23F030019) (LQ23F030019)

浙江理工大学科研业务费专项资金(24222091-Y)National Natural Science Foundation of China(62073296 (24222091-Y)

62006209) ()

Natural Science Foundation of Zhejiang(LQ23F030019) (LQ23F030019)

Fundamental Research Funds of Zhejiang Sci-Tech University(24222091-Y) (24222091-Y)

电子科技

1007-7820

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