Aiming at the problems of blind search in the initial stage， slow convergence speed and easy to fall into local optimum when traditional ant colony optimization is used for path planning of mobile robot， an improved ant colony optimization is proposed. Firstly， according to the distance between each node relative to the connecting line between the starting point and the target point， the initial pheromone is unevenly distributed to make it normal distribution， so as to reduce the blindness in the initial search of the algorithm and speed up the search of the optimal solution. Reduce the blindness of the initial search algorithm， speed up the search of the optimal solution； Secondly， the volatilization factor is improved and the principle of double volatilization factor is adopted to control the volatilization of pheromone， which can not only reduce the possibility of local optimization， but also accelerate the convergence speed. Finally， the redundant path is further optimized to make the path better. The simulation results show that the improved ant colony optimization has faster convergence speed and more stable convergence than the traditional ant colony optimization and other improved ant colony optimizations.