Though larger vessels may be well-equipped to deal with wavy conditions, smaller vessels are often more susceptible to disturbances. This paper explores the development of a nonlinear model predictive control (NMPC) system for Uncrewed Surface Vessels (USVs) in wavy conditions to minimize average roll. The NMPC is based on a prediction method that uses information about the vessel's dynamics and an assumed wave model. This method is able to mitigate the roll of an under-actuated USV in a variety of conditions by adjusting the weights of the cost function. The results show a reduction of 39% of average roll with a tuned controller in conditions with 1.75-metre sinusoidal waves. A general and intuitive tuning strategy is established. This preliminary work is a proof of concept which sets the stage for the leveraging of wave prediction methodologies to perform planning and control in real time for USVs in real-world scenarios and field trials.

There exist a wide range of options for field robotics research using ground and aerial mobile robots, but there are comparatively few robust and research-ready uncrewed surface vessels (USVs). This workshop paper starts with a snapshot of USVs currently available to the research community and then describes "OtterROS", an open source ROS 2 solution for the Otter USV. Field experiments using OtterROS are described, which highlight the utility of the Otter USV and the benefits of using ROS 2 in aquatic robotics research. For those interested in USV research, the paper details recommended hardware to run OtterROS and includes an example ROS 2 package using OtterROS, removing unnecessary non-recurring engineering from field robotics research activities.