Global path planning of AUV based on improved ant colony optimization algorithm
Guang-lei Zhang, Heming Jia · 2012
In order to solve path planning problem for autonomous underwater vehicle(AUV) in the horizontal plane, a new method based on quadtree and improved ant colony algorithm is presented in this paper. Two dimensional horizontal area model can be built by quadtree. An improved ant colony algorithm is adopted for high efficiency path planning based on this model. Quadtree not only records all of the area information but also compresses area information efficiently. Improved ant colony algorithm can find a path that maintains a safe distance from obstacles, which improves the usefulness for the planning path. Simulation experiments illustrated that the designed method can get a good balance between efficiency and usefulness of the planning path and find a path efficiently in the two dimensional horizontal area.