Abstract: In view of the shortcomings of slow rate of convergence and easy to fall into local optimal solution for the tra- ditional ant algorithm, this paper put forward to improve distance heuristic factor to encrease effects on the next node, so as to enhance the global search ability, avoid trap in local optimal solution and improve the rate of convergence. Con- sidering the complexity and diversity of the real environment, this paper introduced multiple path quality constraints to improve the rules of the pheromone update. I}he simulation results show the improved ant colony algorithm has a good effect in the dynamic path planning.

Key words: Dynamic path planning, Ant colony algorithm, Distance heuristic factor, Pheromome update