Robot Dynamic Path Planning Based on Improved A* and DWA Algorithms
Chenxi Guan, Shuying Wang · 2022
When the traditional A* algorithm is applied to robot path planning, it has the problems of low efficiency and unable to avoid obstacles dynamically. In order to solve the above problems, a fusion algorithm based on improved A* algorithm and DWA algorithm is proposed. The A* algorithm is improved in three aspects: reducing the search direction of A* algorithm to reduce the search time, adding path information parameters to dynamically adjust the weight of heuristic function, and introducing important node extraction strategy to reduce the number of turns and shorten the path. Finally, the improved A* algorithm is fused with DWA algorithm. The experimental results show that the improved fusion algorithm can realize global optimal path planning and local real-time obstacle avoidance.