Path Navigation in ACO Using Mobile Robot

Abstract

Ant colony algorithm suffers drawbacks such as slow convergence and easy to trap into local optimum, therefore the path planning for mobile robot based on an improved ant colony optimization algorithm is proposed. The workspace for mobile robot is established with grid method. A hybrid ant colony which is composed of common ants and exploratory ants is utilized to avoid trapping into local optimum. To increase the convergence speed, the pheromone update mechanism is improved by enhancing the sensitivity of the ants to the optimal path with reserving the elite ants. The optimal collision-free path can be planned rapidly in the workspace with multiple obstacles. Simulation and experiment results show that the algorithm is practical and effective.