Multi-AUV target searching under ocean current based on PPSO and velocity synthesis algorithm

One of the challenges for underwater target searching by multi-autonomous underwater vehicles (AUVs) is ocean currents. During the search process different types of ocean currents may impose a negative effect which lengthens search paths and causes more energy consumption. In order to solve this problem, the proposed algorithm in the present paper combines the potential field-based particle swarm optimization (PPSO) and velocity synthesis algorithms. The goal is to control a team of AUVs to search for a target, while guaranteeing that each AUV's motion can offset the impact of ocean currents. Firstly, the fitness function of particle swarm optimization (PSO) was determined by the potential function of the workspace; then, PPSO planned the reasonable paths iteratively; and lastly, the velocity synthesis algorithm kept the AUVs on their planned tracks to offset the influence of ocean currents by adjusting the AUV movement directions. Through simulation studies it was shown that the proposed algorithm is capable of offsetting constant as well as variable ocean currents with higher work efficiency and less energy consumption.