Advancing Marine Autonomy for Remote Aquaculture Sustainment

Lead Pi: Michael Benjamin · 02/2020 - 01/2022

Project number: R/RD-43

PI: Michael Benjamin, MIT Department of Mechanical Engineering
Co-PI: Michael Sacarny, MIT Department of Mechanical Engineering
Additional Personnel: Michael DeFilippo, MIT Sea Grant AUV Lab


Objectives: Develop marine autonomy algorithms for unmanned surface vehicles, to support aquaculture installations. Marine vehicles will be used to test water quality near installations and provide frequent, lower-cost actionable information to aquafarmers. Using remotely operated underwater vehicles deployed from unmanned surface vehicles, we provide operators with an ability to perform remote visual inspection with minimal human effort. Our initial focus will be on oyster farms. Algorithms will be implemented on an existing MIT unmanned surface vehicle leveraging existing MIT open source software. Our objective is develop further algorithms for supporting aquafarming and make these algorithms available to the general public.

Rationale: We will develop algorithms, implemented in C++ in the MOOS-IvP Open Source software paradigm. These algorithms will address safe navigation of a marine vehicle in support of aquaculture missions. They will first be tested in our existing simulation environment, then field tested on the Charles River with the MIT unmanned surface vehicle. In the final stage, we will engage with stakeholders and their marine vehicles to support missions at aquaculture installations.

Methodology: The aquaculture industry has technology gaps that translate into high labor costs on tasks that are dull, dangerous or dirty and uneconomical.  Certain tasks related to water quality sampling, monitoring unauthorized access to installations, and inspection of equipment, offer opportunities for automation with unmanned marine vehicles to make aquaculture safer, more profitable and scalable.