A Multi-Objective Mission Planning Method for AUV Target Search

How an autonomous underwater vehicle (AUV) performs fully automated task allocation and achieves satisfactory mission planning effects during the search for potential threats deployed in space is focus of paper. First, assignment problem defined as a traveling salesman (TSP) with specific distinct starting ending points. Two competitive non-commensurable optimization goals, total sailing distance turning angle generated by AUV to completely traverse threat points planned order, are taken into account. The maneuverability limitations AUV, namely, minimum radius turn speed, also introduced constraints. Then, improved ant colony (ACO) algorithm based on fuzzy logic dynamic pheromone volatilization rule developed solve TSP. With help set, ants that have moved along better paths screened update performed only preferred so enhance pathfinding guidance early stage ACO algorithm. By using rule, more volatile pheromones produced number iterations increases, thus providing effective way escape from local later stage. Finally, comparative simulations presented illustrate effectiveness advantages proposed influence critical parameters analyzed demonstrated.