Aiming at the problems that the traditional ant colony optimization（ACO） algorithm has a slow convergence speed and easy to fall into local optimal solution in path planning of mobile robot

an improved ACO algrithm for path planning of robot is proposed.Environment model is established by the grid method

and the heuristic pheromone matrix is set up based on the artificial potential field

which reduce the blindness of the ants in the initial phase of the search.Excitation function is introduced.Dead-lock phenomenon in search process is reduced.Update mechanism of pheromone is improved

and the impact of excellent ants on global path planning is enhanced. The simulation results show that the proposed improved ant colony algorithm robot path planning algorithm accelerates the convergence speed and has strong robustness and global optimization ability.