Optimal Path Planning of Mobile Robot with Multiple Targets Using Ant Colony Optimization

Abstract

In this paper, we present a path-planning algorithm for mobile robots in an environment with obstacles. We investigate the use of Ant Colony Optimization (ACO) for determining the optimal path for a wheeled mobile robot to visit multiple targets. The environment in which the robot operates is modeled in the form of discrete cells and the robot is modeled as a point robot. The robot has knowledge about the targets' positions but has limited local sensing capability to sense obstacles. The paper investigates the use of multiple autonomous robots for solving the shortest path problem. ACO algorithm is used for dynamic planning of the path to avoid obstacles visit all the targets.