吉林大学学报(信息科学版) ›› 2025, Vol. 43 ›› Issue (4): 792-800.

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基于双向搜索的A*算法与DWA算法融合的路径规划

程鑫a, 李昕光b, 赵士龙b, 郭晓琦b   

  1. 青岛理工大学a. 土木工程学院;b. 机械与汽车工程学院,山东青岛266520
  • 收稿日期:2024-08-01 出版日期:2025-08-15 发布日期:2025-08-15
  • 通讯作者: 李昕光(1978— ), 女, 山东茌平人, 青岛理工大学副教授, 硕士生导师, 主要从事自动驾驶研究,(Tel)86-18145628997(E-mail)xinguangli@ qut. edu. cn。 E-mail:chx8991@163. com
  • 作者简介:程鑫(1998— ), 男, 山东平度人, 青岛理工大学硕士研究生, 主要从事车辆路径规划研究, (Tel)86-15662658185 (E-mail)chx8991@163. com
  • 基金资助:
    山东省自然科学基金资助项目(ZR2020MG017)

Path Planning Based on Integrating Bi-Directional A* and DWA Algorithm

 CHENG Xina, LI Xinguangb, ZHAO Shilongb, GUO Xiaoqib   

  1. a. School of Civil Engineering; b. School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266520, China
  • Received:2024-08-01 Online:2025-08-15 Published:2025-08-15

摘要: 为提高传统A*算法在路径规划时的实时性和安全性,提出了一种融合改进A*DWA(DynamicWindow Approach)的路径规划方法。 首先, A*算法的搜索邻域进行了优化, 以减少节点的搜索方向; 其次, 引入 双向搜索和动态定义目标节点策略优化搜索机制,从起始和目标节点进行双向路径搜索;引入动态权重系数, 减少路径搜索过程中产生的冗余节点,并通过贝塞尔曲线对路径进行平滑处理;最后,将改进A*算法与DWA 算法相融合,以规避随机障碍物。利用PyCharm进行仿真,结果表明,与其他两种算法相比,改进A*算法搜索 节点减少46.25%以上, 搜索时间减少了24.06%以上, 融合算法能避开随机障碍物, 且规划路径的平滑性和 安全性都有较大提升。

关键词: 改进A*算法, DWA算法, 双向搜索策略, 路径规划

Abstract:

In order to improve the real-time performance and security of the traditional A* algorithm during path planning, a path planning method incorporating improved A* and DWA(Dynamic Window Approach) is proposed. Firstly, the search neighborhood of the A* algorithm is optimized to reduce the search direction of nodes. Secondly, the search mechanism is optimized by introducing bidirectional search and dynamically defining the target node strategy to carry out bidirectional path searching from the start node and the target node. Dynamic weighting coefficients are introduced to reduce the generation of redundant nodes in the process of path searching, and the paths are smoothed by the Bezier curves. And lastly, the improved A* algorithm is fused with the DWA algorithm to realize dynamic obstacle avoidance. Simulation is carried out using PyCharm, and the results show that, compared with the other two algorithms, the search nodes of the improved A* algorithm are reduced by more than 46.25%, and the search time is reduced by more than 24.06%. The integrated algorithm is able to realize dynamic obstacle avoidance, and the smoothness and safety of the planned paths have been improved.

Key words: improved A* algorithm, dynamic window approach ( DWA) algorithm, bidirectional search strategy, path planning

中图分类号: 

  • TP242