To solve the problems of low search efficiency, interspersed obstacles, unsmooth paths, and inability to avoid unknown obstacles in the traditional A* algorithm during path planning, a mobile robot dynamic obstacle avoidance method integrating the improved A* algorithm with the improved DWA algorithm is proposed. In the improved A* algorithm, the global obstacle occupancy ratio is introduced, dynamic weight coefficients are added to the heuristic function, the search field is optimized, the safe distance is set to remove redundant nodes, and third-order Bessel curves are added to smooth the paths, and the cost subfunctions of the target points are added to the DWA algorithm and the coefficients of the cost function are dynamically adjusted. The dynamic obstacle avoidance of the mobile robot is realized. Simulation results show that in different environments, compared with the traditional A* algorithm and other improved A* algorithms, the path length of the improved A* algorithm in this paper is shortened by an average of 5.14% and 1.01%, the search nodes are reduced by 57.05% and 36.59%, and the planning time is reduced by 34.39% and 8.49%, respectively; the improved fusion algorithm in this paper is reduced by an average of 5.14% and 1.01%, the search node is reduced by 57.05% and 36.59%, and the planning time is reduced by 34.39% and 8.49%, respectively. other fusion algorithms, the path length is shortened by 19.89% and 1.82% on average, and the planning time is reduced by 53.66% and 13.01% on average, respectively. It is proved that the improved fusion algorithm proposed in this paper effectively shortens the planned path length and time, and is able to realize real-time obstacle avoidance in complex dynamic environments to satisfy the high efficiency and safety of mobile robots during traveling.