Abstract: To realize path planning in complicated environments,a new potential field optimal ant colony algorithm for path planning was presented.To further quicken the convergence speed of AC,the path planning results of potential field method were taken as the prior knowledge,and the original reached grids were initialized by neighborhood pheromone.The potential field guided weight was constructed to change transition probability as well,thus it can be active over the entire period of path searching,and can get rid of blindness.Simulation results indicate that the proposed algorithm(APF-AC) is characterized by high convergence speed,short planning path and self-adaptive.

Key words: Path planning,Ant colony algorithm,Artificial potential field,Transition probability,Guided weight computer