Aiming at the problems of low search efficiency, poor path smoothness and security of A* algorithm, and low real-time pathfinding efficiency of DWA integrated with global path planning algorithm, a hierarchical smooth optimization A* guided DWA (HSA*-G-DWA) path planning method for mobile robots is proposed. Firstly, the double dynamic weighting factor is introduced into the cost function of A* algorithm and the collision constraint is developed to avoid the search of unrelated extension nodes, so as to improve the efficiency and security of path search. Secondly, the hierarchical smoothing optimization strategy is designed to eliminate redundant nodes and turning nodes in the path, and reduce the number of path nodes and the path length. After that, the initial global path is generated by segmented interpolation of lines without any obstacle constraints and arcs with obstacle constraints to ensure the safety and smoothness of the path. Then, if the mobile robot encounters unknown obstacles in the process of tracking the global path, it uses the global path to guide DWA to generate the local dynamic correction path for obstacles avoidance and returning to the remaining global path, which reduces the amount of real-time calculation. Finally, the simulation results show that the path search time and path nodes of the proposed HSA*-G-DWA algorithm are reduced by 88.43% and 86%, respectively, and the smoothness and security of the path are better than the A* algorithm in the static environment; and the HSA*-G-DWA algorithm can avoid unknown obstacles in the unknown environment in real time. Compared with the DWA algorithm, Dijkstra algorithm, RRT algorithm and other fusion algorithms, the path length is reduced by 25.78%, 18.65%, 30.48% and 14.59% on average, and the path search time is reduced by 67.39% on average.