【】Aiming at obstacle avoidance path planning of mobile robot, an improved gray wolf optimization algorithm is proposed based on the basic swarm intelligence algorithm. The test function proves the stability, accuracy and convergence of the algorithm. Then it is applied to obstacle avoidance path planning of mobile robot for the first time. By studying the obstacle avoidance path of mobile robot with improved gray wolf optimization algorithm, it is compared with basic gray wolf optimization algorithm, particle swarm optimization algorithm and genetic algorithm. The simulation results show the stability, accuracy and convergence of the algorithm, which is of great significance in the field of path planning.□□□□□□□