Intelligent Navigation of Autonomous Underwater Vehicles for Cage Aquafarm Surveillance

Cage aquafarm systems need to provide artificial monitoring and control functions to maintain essential environmental factors for the high productivity of marine products. Autonomous underwater vehicles (AUVs), which have been utilized for various ocean applications such as coastal structure inspection and undersea exploration, are emerging as effective candidate tools for aquafarm surveillance due to their capability of broad range navigation. This paper proposes a technique for intelligent navigation of AUVs around cage aquafarms based on the artificial immune technology. We adopt a clonal selection algorithm(CSA) to determine optimal navigation paths surrounding the aquafarms while reducing energy consumption.