An Improved Ant Colony Algorithm For Mobile Robot Path Planning

Abstract

An improved ant colony algorithm is proposed for robot path planning under a static environment.Grid method is used to establish workspace model of the robot.By simulating the foraging behavior of ant colony,search for optimal path is completed with the way of fold-back iterating between the start and target point for ants,and diversity of the search is enhanced.Inertia principleand the strategy of the most pheromone search are used to make ants more sensitive to the optimal path during the searching process.Meanwhile,according to the features of the pheromone strewing in the grids,a new strewing method and updating strategy of pheromone is reconstructed to accelerate convergence of the solution.Validity of the proposed algorithm,with which optimal path can be planned rapidly even in the geographic conditions with obstacles exceedingly complicated,is demonstrated by the simulation results.