Abstract: Aiming at the efficiency of path planning of mobile robots in complex environments (includ- ing static and dynamic environments), a hybrid algorithm combining an improved A* algorithm and an improved dynamic window method is proposed. Aiming at the problem of insufficient security of the traditional A* algorithm, the obstacle avoidance strategy is adopted to optimize the selection of  nodes to increase the safety of the path. Aiming at the problem of many turning points, the recursive dichotomy optimization strategy is adopted to remove redundant nodes and reduce the number of turns. Aiming at the problem of insufficient path smoothness in a static environment, the dynamic inscribed circle smoothing strategy is used to optimize the polyline angle to a radian angle to increase the smoothness of the path. In the traditional dynamic window method, when there are obstacles near the target point, the planning effect is not good and it is easy to fall into the local optimum in the concave groove obstacle. The distance deviation and trajectory deviation are introduced into the original evaluation function. Finally, the proposed improved A* algorithm and hybrid algorithm are simulated and compared with other algorithms in static and dynamic environments respectively. The results show that, compared with the traditional hybrid algorithm, the proposal reduces the path length and running time in the temporary obstacle environment by 13.2% and 65.8%, respectively, and reduces the path length and running time in the mobile obstacle environment by 13.9% and 44.9%, respectively. The proposed algorithm improves the efficiency of path planning in complex environments. 

Key words: mobile robot, path planning, improved A* algorithm, dynamic window method