Path planning for robots utilizing the enhanced A* and improved dynamic window approach algorithm

Abstract

To address the issues of low search efficiency and the inability to dynamically avoid unknown obstacles in complex environments during mobile robots' path planning, a novel approach called the F_TSEA_IDWA algorithm is introduced to tackle these challenges effectively. The F_TSEA_IDWA algorithm is a fusion of two improved algorithms, namely TSE_A* and DWA. Initially, the TSE_A* algorithm is employed to conduct global path planning, followed by the extraction of path nodes generated by the TSE_A* algorithm as intermediate target points for the enhanced DWA algorithm. Subsequently, the improved DWA algorithm is applied to perform local dynamic path planning. Experimental results reveal that the F_TSEA_IDWA algorithm not only avoids local optima and reaches the endpoint successfully, but also effectively avoids unknown obstacles and enhances the dynamic obstacle avoidance performance of mobile robots in complex environments. Thus, the proposed fusion algorithm offers a viable solution for the path planning of mobile robots.