Intelligent Navigation and Control of a Prototype Autonomous Underwater Vehicle for Automated Inspection of Aquaculture net pen cages

Aquaculture is one of the fastest growing food sectors worldwide providing more than 50% of world fish consumption. Towards sustainable development, aquaculture ought to design and implement technical solutions for the efficient management of farms, thus improving fish performance and decreasing operational costs, human effort and environmental impact. For this, periodic inspection of fish-cages along with early warning systems are required, functionalities that small-sized underwater vehicles can provide. In this paper, an efficient methodology for intelligent navigation of an Autonomous Underwater Vehicle (AUV) architecture is presented, yielding to a useful tool with advanced capabilities in terms of automated manipulation via real-time optical recognition approaches, miniaturization of sensors and processing units, selective monitoring, data recording/transmission operations and proper parameter calculations for further offline-analysis of captured information. The proposed AUV system constitutes an increased Technology Readiness Level version of the preliminary prototype designed earlier by our group, incorporating additional modules and application capabilities, focusing on regular periodic fish-cage net inspection in terms of net holes and fouling. The optical navigation scheme has been tested in laboratory installations under numerous scenarios so as to determine the factors affecting its robustness and efficiency. Results extracted under the validation procedure in operational conditions indicate that the proposed framework can prove a cost-effective, flexible and operative solution for aquaculture industry, enabling the transfer of operations further offshore.