A novel robust algorithm for path planning of multiple autonomous underwater vehicles in the environment with ocean currents

Path planning of multiple autonomous underwater vehicles (AUVs) is the premise to complete large-scale marine geophysical exploration, military reconnaissance and so on. However, the disturbance of ocean currents has an important effect on the performance of the multi-AUVs path planning and cannot be ignored in practice. Path travel time, smoothness and safety factor are set as the objective functions of multi-AUVs path planning in this paper. An improved 'min-max' multiple traveling salesmen problem (MTSP) robust path planning model is proposed for multiple AUVs under ocean currents, which is designed to obtain the best solution with the worst case. The cooperative genetic algorithm is proposed to obtain a cluster of optimal paths for multiple AUVs. The results show that the proposed algorithm makes the path planning with strong robustness for the multi-AUVs in the environment with ocean currents. The proposed algorithm in this paper has better performance than existing methods for the multi-AUVs path planning with ocean currents.