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Optimal Harvesting with Autonomous Tow Vessels for Offshore Macroalgae Farming

Bhabra, M.S., M. Doshi, P.J. Haley, Jr., C. Mirabito, B.C. Koenig, P.F.J. Lermusiaux, C.A. Goudey, J. Curcio, D. Manganelli, and H. Goudey, 2020. Optimal Harvesting with Autonomous Tow Vessels for Offshore Macroalgae Farming. In: OCEANS '20 IEEE/MTS, 5-30 October 2020, sub-judice.

Offshore framing has, in the past few decades, started to gain increasing popularity. However, a key determinant for its future success as an industry is the ability to substitute traditional low-tech and labor-intensive tools and methods with automation and technology-driven solutions. Autonomous underwater and surface vehicles, which have been gaining prevalence in numerous marine applications such as naval security, scientific exploration and ocean mapping, have started to also be considered in the aquafarming industry. The use of unmanned vessels, or autonomous ocean tractors, can provide high towing efficiency while simultaneously significantly lowering the cost of operation (Goudey and Associates, 2020).

Central to the optimal control of these autonomous vessels for efficient offshore macroalgae farming are two key components: ocean forecasting and route planning. Specifically, there is a need for accurate prediction of (i) the dynamic ocean environment including physical transports and macroalgae ecosystem dynamics, and (ii) the paths of the autonomous vessels that optimally manage and harvest the algae. The dynamic effects of the ocean environment on both the algae and the relatively slow vessels are major differences with respect to classic farming on land. In this work, we address these two components and propose a framework for exact optimal harvesting of algae fields using autonomous tow vessels. We showcase both free-flowing algae and fixed or enclosed algae in this optimal dynamic farming.