计算机与现代化 ›› 2022, Vol. 0 ›› Issue (01): 103-107.

• 人工智能 • 上一篇    下一篇

融合改进A*与DWA算法的移动机器人路径规划

  

  1. (沈阳化工大学信息工程学院,辽宁沈阳110142)
  • 出版日期:2022-01-24 发布日期:2022-01-24
  • 作者简介:庞永旭(1995—),男,山东禹城人,硕士研究生,研究方向:机器人路径规划,E-mail: 2726668090@qq.com; 袁德成(1960—),男,内蒙古阿拉善左旗人,教授,博士,研究方向:复杂系统建模,优化与控制。
  • 基金资助:
    国家重点研发计划项目(2018YFB1700200)

Mobile Robot Path Planning Based on Fusion of Improved A* and DWA Algorithms

  1. (College of Information Engineering, Shenyang University of Chemical Technology, Shenyang 110142, China)
  • Online:2022-01-24 Published:2022-01-24

摘要: 针对移动机器人在复杂环境下实现全局路径最优、未知环境下动态实时避障这一路径规划需求,对传统A*(A-star)算法进行改进,并融合动态窗口法(DWA)实现动态实时避障。首先分析栅格环境下的障碍物占比,将障碍物占比引入传统A*算法,优化启发函数h(n),从而改进评价函数f(n),提高其在不同环境下的搜索效率;其次针对复杂栅格环境下传统A*算法优化后的轨迹与障碍物顶点相交问题,优化子节点选择方式,同时删除路径中的冗余节点,提高路径的平滑度;最后融合动态窗口法,实现复杂环境下移动机器人的动态实时避障。通过MATLAB下的对比仿真实验表明,改进算法在轨迹长度、轨迹平滑度以及历经时间上得到优化,满足全局最优且能实现动态实时避障,具有更优秀的路径规划效果。

关键词: 移动机器人, A*算法, DWA, 实时避障

Abstract: Aiming at the path planning requirements of mobile robot to achieve global optimal path in complex environment and dynamic and real-time obstacle avoidance in unknown environment, the traditional A* (A-star) algorithm is improved, and Dynamic Window Approach (DWA) is integrated to achieve dynamic and real-time obstacle avoidance. Firstly, the obstacle proportion in the grid environment is analyzed. The obstacle proportion is introduced into the traditional A* algorithm to optimize the heuristic function h(n), so as to improve the evaluation function f(n) and improve its search efficiency in different environments. Secondly, in view of the intersection between the trajectory and the vertex of obstacles optimized by the traditional A* algorithm in the complex grid environment, the selection method of child nodes is optimized, and the redundant nodes in the path are deleted to improve the smoothness of the path. Finally, Dynamic Window Approach is integrated to realize dynamic and real-time obstacle avoidance of mobile robot in complex environment. The comparative simulation experiments under MATLAB show that the improved algorithm is optimized in the path length, path smoothness and elapsed time, meets the global optimal and can realize dynamic and real-time obstacle avoidance, and has better path planning effect.

Key words: mobile robot, A* algorithm, DWA, real-time obstacle avoidance