Aiming at the problem of local minimum and unreachable target when using artificial potential field method for mobile robot path planning in the presence of complex obstacles. In this paper, an improved artificial potential field method based on concave obstacle patching is proposed for local path planning. Firstly, the concave obstacles are filled to prevent the robot from entering the local minimum area. Then, by adding the distance influence factor, the repulsion field function is improved to make the target point the smallest point in the global situation field, and prevent the robot from falling into the target unreachable area. Finally, the simulation results show that the improved artificial potential field method proposed in this paper can solve the local minimum problem and the target unreachable problem in the environment with complex obstacles. Compared with other algorithms, it can effectively reduce the path compensation and improve the planning efficiency.