Energy-Optimized Path Planning for Fully Actuated AUVs in Complex 3D Environments

This paper presents an energy-optimized path planning approach for fully actuated autonomous underwater vehicles (AUVs) in three-dimensional ocean environments to enhance their operational range and endurance. A fully actuated AUV is characterized by its high degrees of freedom and precise controllability. Using real terrain data, we construct environmental models incorporating a Lamb vortex and random obstacles. We develop a mathematical model of the AUV’s total energy consumption, accounting for constraints imposed by its fully actuated design and extensive maneuverability. To minimize energy usage, we propose an energy-optimized path planning algorithm that combines energy-optimized particle swarm optimization (EOPSO) and sequential quadratic programming (SQP). The proposed method identifies the optimal path for energy consumption and the corresponding optimal surge speed. The efficacy of the algorithm in optimizing the total energy consumption of the AUV is demonstrated through the simulation of various scenarios. In comparison to other algorithms, paths planned by this algorithm are shown to have superior robustness and optimized energy consumption.