Research on Dynamic Path Planning of Traffic Isolation Robots by Improving A* and DWA

To address the issues of low search efficiency and insufficient path safety when applying the traditional A* algorithm to traffic isolation robots, this study proposes a solution that integrates an improved A* algorithm with the Dynamic Window Approach (DWA). The core improvements include the introduction of a 4+6 neighborhood search strategy, an angle-optimized search strategy, a dynamic weight search priority factor (SPF), and a bidirectional A* algorithm. Through Matlab simulation and physical platform verification, the results show that the improved A* algorithm significantly reduces the number of dangerous points on the path, with the average search time reduced by 66.55% and the average number of expanded nodes decreased by 39.84%. Meanwhile, the algorithm that combines the improved A* and DWA can effectively guide the traffic isolation robot to precisely navigate to the target point and avoid unknown obstacles in real time during the journey.