The traditional ant colony algorithm in the process of mobile robot path planning,the algorithm is easy to fall into the local optimization problem when the convergence of the algorithm. Aiming at this problem,a new ant colony optimization for mobile robot path planning method is proposed. Firstly,the mathematical model of the robot path planning is established. Based on this,the traditional ant colony algorithm is improved,and the local robot path information is introduced into the initialization of ant colony pheromone and the probability of path selection,which improves the convergence speed of ant colony algorithm and prevents premature. By introducing the crossover operation and adjusting the parameters of the ant colony algorithm,the algorithm can avoid local optimization. The simulation results show that the proposed method can significantly improve the optimal path search capability,the overall performance is better than the traditional ant colony algorithm.