Computer Integrated Manufacturing System ›› 2024, Vol. 30 ›› Issue (1): 184-195.DOI: 10.13196/j.cims.2021.0498

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Path planning by integrating improved A* algorithm and optimized dynamic window approach

ZOU Wen1,HAN Bingchen2+,LI Pengfei2,TIAN Jianfeng2   

  1. 1.Department of Computer,Taiyuan Normal University
    2.Department of Physics,Taiyuan Normal University
  • Online:2024-01-31 Published:2024-02-04
  • Supported by:
    Project supported by the National Natural Science Foundation,China(No.11805141),the Application Basic Research Programs of Shanxi Province,China(No.201901D211424,201901D111293),and the Postgraduate Education Innovation Foundation of Taiyuan Normal University,China(No.SYYJSJC-2171).

融合改进A*算法和优化动态窗口法的路径规划

邹文1,韩丙辰2+,李鹏飞2,田剑锋2   

  1. 1.太原师范学院计算机系
    2.太原师范学院物理系
  • 基金资助:
    国家自然科学基金资助项目(11805141);山西省基础应用研究资助项目(201901D211424,201901D111293);太原师范学院研究生教育创新资助项目(SYYJSJC-2171)。

Abstract: To solve the problems of traditional A* algorithm,including excessive turning points,overmuch time consumption,and the lack of flexibility of dynamic window approach in complex environment,a path planning algorithm based on the combination of improved A* algorithm and optimized dynamic window approach was proposed.A topology map with larger granularity was built on the traditional grid map,and then the paths planned by the topology layer were optimized on the grid map to remove redundant nodes and improve the smoothness of the paths.The dynamic window approach was optimized by increasing the motion states of the robot in different scenarios.The key point of global planning was taken as the temporary target point of local planning to realize the fusion of the two algorithms.The comparative experiments showed that the fusion algorithm not only ensured the optimal global path but also reduced the number of turning points and time consumption.Additionally,it improved the smoothness and flexibility of the robot's path in dynamic environment.

Key words: mobile robot, path planning, improved A* algorithm, optimization dynamic window approach

摘要: 针对传统A*算法在栅格数量较多时存在折点多、耗时长,以及动态窗口法在复杂环境下灵活性差的问题,提出一种融合改进A*算法和优化动态窗口法的路径规划算法。首先,在传统栅格地图上建立一层粒度值更大的拓扑层地图,接着将拓扑层规划出的路径在栅格地图上进行优化,删除冗余节点、提高路径平滑度。通过增加机器人在不同场景下的运动状态来优化动态窗口法。最后,将全局规划的关键点作为局部规划的临时目标点,实现两种算法的融合。通过对比试验,证明融合算法不仅保证了全局路径较优而且减少了折点数、耗费时间,还提高了机器人在动态环境下路径的平滑度和灵活性。

关键词: 移动机器人, 路径规划, 改进A*算法, 优化动态窗口法

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