Mobile Robot Path Planning Using Ant Colony Algorithm

Abstract

Path planning for the mobile robot is to find a shortest obstacle free path from the starting position to the target position. Ant colony optimization method is frequently used to obtain the optimal path in the static known environment. But local minimum and slow convergence are the main problems of ant colony algorithm. This paper proposes a modified ant colony algorithm for path planning of the mobile robot in a known static environment. The modified ant colony algorithm can enlarge the searching range so that the local minimum problem can be weakened, while the algorithm can also converge quickly. And in the optimal path searching process, the turning factor is considered, too. The obtained optimal path has not only short distance, but also few big turning positions. Simulations are done to verify the proposed modified ant colony algorithm.