基于改进型 A* 和 DWA 的机器人路径规划算法

Haisheng Song, Deyang Zhang
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摘要

针对传统路径规划中 A* 算法搜索效率低、冗余点多、无法在复杂环境中实时避开未知障碍物等问题,本文提出了一种基于 A* 算法并结合动态窗口法(DWA)的路径规划算法。首先,改进了传统 A* 算法的评估函数和子节点的扩展策略,提高了全局路径的安全性和搜索效率。然后,对全局路径中的冗余节点进行处理,减少转弯点的数量,提高全局路径的平滑度,改善机器人在行进过程中的不稳定性和能耗;最后,在全局路径规划的基础上,引入 DWA 算法,进行局部未知环境下的路径规划。通过保留关键路径转折点作为中间路径引导,完成局部路径规划。实时避障。通过仿真实验,验证了融合算法的有效性和可行性。
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Robot Path Planning Algorithm based on Improved A* and DWA
Aiming at the problems of low search efficiency of A* algorithm in traditional path planning, many redundant points, and inability to avoid unknown obstacles in real-time in complex environments, this paper proposes a path planning algorithm based on A* combined with Dynamic Window Approach (DWA) algorithm. First, the evaluation function of the traditional A* algorithm and the expansion strategy of sub-nodes are improved to improve the safety and search efficiency of the global path. Then the redundant nodes in the global path are processed to reduce the number of turning points and improve the smoothness of the global path. to improve the instability and energy consumption of the robot during travel; finally, based on the global path planning, the DWA algorithm is introduced to perform path planning in the local unknown environment. The local path planning is completed by retaining the key path turning points as intermediate path guidance. Real-time obstacle avoidance. Through simulation experiments, the effectiveness and feasibility of the fusion algorithm are verified.
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