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.

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integrated algorithm glasius bioinspired neural network gbnn underwater vehicles cooperative team environments target search and tracking in unknown search for static or dynamic targets bioinspired cascaded tracking control approach tracking of different trajectory tracking errors search efficiency

Gene Eu Jan, Hongbing Sun,Xiang Cao,.Multi-AUV cooperative target search and tracking in unknown underwater environment. 150 (0),.

Gene Eu Jan, Hongbing Sun,Xiang Cao,"Multi-AUV cooperative target search and tracking in unknown underwater environment" 150

Gene Eu Jan, Hongbing Sun,Xiang Cao,"Multi-AUV cooperative target search and tracking in unknown underwater environment"