An Improved Ant Colony System Algorithm for Optimal Path Planning Problem of Mobile Robots

In this paper, we consider the path planning problem of mobile robots. A method was proposed in a recent paper for the real-time globally optimal path planning of mobile robots, in which the MAKLINE graph is built to describe the working space of the mobile robot, the Dijkstra algorithm is used to obtain the shortest path from the start point to the goal point in the MAKLINE graph, and an ant colony system (ACS) algorithm is adopted to get the best path. We present an improved ACS algorithm based on dynamic partitioning and new heuristic function involved in angle to optimize the sub-optimal path obtained by Dijkstra algorithm. Simulation results show that the improved algorithm is effective, which has the faster convergence speed and can get a shorter path than the original method.