Research on ROS Robot Path Planning by Integrating and Improving A* and DWA Algorithms
Jiahao Yu, Zhisheng Zhang, Min Dai, Zhijie Xia, Haiying Wen, Liguo Shuai · 2025
With the improvement of industrial automation and intelligence levels, ROS mobile robots are increasingly being used in industrial production, and their path planning capabilities directly affect task execution efficiency and safety. This paper proposes a collaborative path planning method that combines the improved A* algorithm with the dynamic window method (DWA) to address the problems of the traditional A* algorithm prone to falling into local optima, high path redundancy, and excessive turning points in complex environments. Firstly, the improved A* algorithm significantly reduces path redundancy and turning frequency by introducing a 5*5 neighborhood search strategy, a heuristic function based on dynamic optimization of obstacle density, and a dynamic safety threshold screening mechanism, and achieves path smoothing by using a reverse redundant node deletion strategy; Secondly, the improved A* algorithm is integrated with the DWA* algorithm to construct a global path planning and local dynamic obstacle avoidance synergy mechanism, taking into account both global optimality and real-time obstacle avoidance capability. Simulation experiments show that compared with the traditional A* algorithm, the improved A* algorithm shortens the path length by 4.09%, reduces the number of turns by 42%; After integrating the DWA* algorithm, the robot was able to efficiently plan the global path and avoid obstacles in real time in a dynamic obstacle environment, verifying the feasibility and robustness of the algorithm. This study provides an efficient and safe solution for autonomous navigation of ROS robots in complex environments.