Mobile Robot Path Planning Based on Improved A^* Algorithm and Dynamic Window Method

A hybrid algorithm combining the improved A^* algorithm and the dynamic window method is proposed, to solve the problem of mobile robot path planning in multi-target complex environments. In order to improve the algorithm efficiency by planning a path passing through multiple target points in a single run, and to improve the flexibility of path smoothing and meet the non-holonomic constraints of mobile robots, the target cost function is used to prioritize all targets firstly. Furthermore, the improved A^* algorithm is used to plan an optimal path passing through multiple target points. Meanwhile, the adaptive arc optimization algorithm and the weighted obstacle step adjustment algorithm are used to effectively shorten the path length by 5% and reduce the total turning angle by 26.62%. Secondly, an online path planning method combining the improved dynamic window algorithm and the global path planning information is proposed for mobile robots to avoid the local obstacles and pursue the dynamic target points in dynamic complex environments. The preview-deviation-yaw based tracking method is used to successfully capture the moving target points and improve the path planning efficiency. Finally, the simulation experiments with the proposed method are carried out, and the results show that it can achieve the path planning more effectively in complex dynamic environments.