Using Cellular Ant Colony Algorithm for Path-Planning of Robots

Abstract

To overcome some shortcoming existed in the conventional ant colony algorithms, e.g. slow converging and trend for falling into local convergences, a novel method for robot path planning is introduced based on cellular ant colony. Firstly, two ant colonies were set to run with different strategies. Secondly, the existing ant colony paths were evolved by following the cellular rules, so that the ants could jump from the current region into the region with a solution. Experiment results showed that the proposed algorithm proved to be stable, and that the global optimal path was found in a short time in a number of iterations.