To solve the problems of traditional path planning algorithms, such as low efficiency in path planning, unsmooth paths, and poor dynamic obstacle avoidance, this paper proposes a path planning method that combines the A* algorithm with the APF algorithm. For the A* algorithm, a dynamic weighting method is used to adjust the weight of the heuristic function according to the position of the traveling robotic fish and the distance between the robotic fish and the obstacles as an index; then the Gaussian filtering method is used to curve-smooth the obtained optimal path. Then the path generated by the improved A* algorithm is used as the search path of the APF algorithm, and dynamic obstacle avoidance is carried out on the basis of realizing the shortest path planning. The results of simulation experiments show that the improved A* algorithm obstacle different maps, the average reduction of the search time is 52.32%, the average reduction of the number of search nodes is 56.60%, the average reduction of the path length is 6.33%; under different sizes of maps, the average reduction of the number of search nodes is 49.60%, the average reduction of the search time is 40.89%, the average reduction of the path length is 5.55%. The fusion algorithm can perform successful dynamic obstacle avoidance and path planning under maps with dynamic obstacles.