Multi-AUV cooperative target search and tracking in unknown underwater environment

Abstract

For target search and tracking in unknown underwater environment, an integrated algorithm for a cooperative team of multiple autonomous underwater vehicles (Multi-AUV) is proposed by combining the Glasius bio-inspired neural network (GBNN) and bio-inspired cascaded tracking control approach to improve search efficiency and reduce tracking errors. Among them, the GBNN is mainly used to control a multi-AUV team in search of each targets. Once any target is found, the bio-inspired cascaded tracking control approach is applied to track it in case that it may escape. This integrated algorithm deals with various situations such as search for static or dynamic targets, and tracking of different trajectory in underwater environments with obstacles. The simulation results show that this integrated algorithm is of high efficiency and adaptability.