Energy efficient path planning of autonomous underwater vehicles for environment modeling

In this paper, we propose a path planning method of autonomous underwater vehicles (AUV) for exploring the uncertain environment, which aims to minimize the estimation uncertainty and the total energy-consumption. Grid based environment model is used for the path planning problem. Kalman filter is employed to handle the measurement information and the AUV is driven to the optimal direction which minimize the filter uncertainty and the energy consumption. Simulation results are provided to show the efficiency of our algorithm.