Optimal ASV Path-Following for Improved Marine Survey Data Quality

Marine geophysical surveys are one of the methods utilized to map the seabed or water column for a variety of use cases. Multibeam echosounders (MBES), sidescan sonar (SSS), and subbottom profilers (SBP) are examples of instruments used to accurately quantify or georeference seafloor characteristics for applications such as navigation safety/keel clearance, offshore wind or coastal scientific studies. Autonomous vehicles can collect similar quality data to that collected by a large vessel at a fraction of the cost and human involvement and with a much smaller carbon footprint. This paper builds upon previous work [1] and proposes a new path-following control approach for an autonomous surface vehicle (ASV) using a more realistic kinematics model that includes lateral drift. The performance of the new controller is verified through simulations and field testing showcasing the improvement in the vessel’s motion and the acquired sonar data.