Aiming at the problems of collision or failure of path planning when the robot uses the A ∗ algorithm to plan a path in the environment with random obstacles, a random obstacle avoidance method for robots that combines the improved A ∗ algorithm with the dynamic window method is proposed. In the improved A ∗ algorithm, firstly, the search point selection strategy and the evaluation function are optimized to improve the search efficiency of the A ∗ algorithm, then the redundant point deletion strategy is proposed to eliminate the redundant nodes in the path, and the dynamic window method is used for the local planning between every two adjacent nodes to ensure that on the basis of the global optimal path, random obstacle avoidance is achieved in real time, so that the robot can reach the target point successfully. The experiment results show that the improved A ∗ algorithm proposed in this paper can reduce the path length by 4. 39% and the calculation time by 65. 56% on average compared with the traditional A ∗ algorithm. After fusing the dynamic window method, on the global path basis the local path can be modified to achieve random obstacle avoidance, which verifies the effectiveness of the proposed algorithm.