Path planning and tracking for AUV in large-scale environment

In this paper new method of path planning for autonomous underwater vehicle (AUV) in large-scale underwater environment is presented. The main idea behind this method is to make full use of the local real-time environment information, partition global working environment dynamically and optimize each local area using Fast Marching algorithm (FM), finally generate a global quasi-optimal path from start to the destination. Simulation shows this method is of good performance in convergency and reliability, can fulfill demand of the experiment. Furthermore, path tracking algorithm based on kinematics model and hydrodynamics model of AUV in the case of depth-fixed is designed. The effectivity of proposed methods is validated my simulation experiments.