In order to realize the autonomous navigation of mobile robot in dynamic environment, DWA algorithm is used to avoid local obstacles based on the global optimal path planned by ant colony algorithm. The initial pheromone of the adjacent grids is calculated according to the distance from the obstacle grid, and the principle of uneven distribution of the initial pheromone is proposed; the heuristic function is improved by adaptive adjustment to improve the search rate of the algorithm; the wolf group rule is used to improve the pheromone update mode, and the optimal, worst and ordinary layer ants are classified and updated to improve the optimization ability of the algorithm; The method of secondary path optimization is used to effectively reduce the length of the path and improve the smoothness of the path; Taking the key points of the global planning path of the ant colony algorithm as the target points, the DWA algorithm is used for local path planning. The simulation results show that the improved fusion algorithm can reduce the length of the optimal path, reduce the number of turns and effectively avoid obstacles.