When the traditional artificial potential field algorithm is used for path planning in an old warehouse, defects such as collision with obstacles far from the target, an unreachable target point, and local minimums, which originally appear infrequently, occur much more frequently. To improve the success rate of the artificial potential field algorithm in path finding in an old warehouse, this paper proposes an improved artificial potential field algorithm that corrects the above three defects and uses Matlab simulation to verify the effectiveness of the algorithm. In the improved artificial potential field algorithm, the problems of collision with obstacles far from the target and an unreachable target point are solved through the improvement of gravitation and repulsion. The local minimum problem is effectively solved by introducing temporary obstacles. In the experimental part, for different simulation environments, we use path length and program running time as evaluation indicators to compare the path planning effects of the traditional artificial potential field algorithm and the improved artificial potential field algorithm. Experimental results show that the improved algorithm always outperforms the traditional algorithm regardless of the presence or absence of defects in the environment.