Planetary rover path-planning based on ant colony optimization algorithm

In order to navigate through unstructured planetary environment autonomously, a path-planning algorithm based on ant colony optimization (ACO), goal-oriented behavior, inertial behavior and obstacle-following behavior are added to ant individual of ACO. By executing behavior weighted fusion, ACO planning algorithm is improved and used to resolve planning problem of planetary rover. Furthermore, a tight-line algorithm is presented, to give a shortest path from start point to the exploration site by processing the path-planning result of ACO. The simulation result shows of the path planning algorithm.