SeaVis: Modeling and Control of a Remotely Operated Towed Vehicle for Seabed Visualization and Mapping
For underwater robotics researchers, this work provides an improved control method for ROTVs, though it is incremental as it applies existing control techniques to a specific vehicle model.
This paper models a remotely operated towed vehicle (ROTV) for seabed mapping and develops a gain-scheduled LQR controller that outperforms PID in simulation, achieving superior robustness, control efficiency, and reduced flap actuation.
High-resolution seafloor mapping necessitates stable and precise positioning for underwater robots. This paper introduces a novel mathematical model for SeaVis remotely operated towed vehicles (ROTVs) and develops a gain-scheduled linear-quadratic regulator (LQR) for robust depth and attitude control. We validate the approach in a high-fidelity simulation, benchmarking the LQR against a conventional PID controller over a challenging seabed profile. The presented results demonstrate the LQR's superior performance, with significantly enhanced robustness to disturbances, greater control efficiency, and substantially reduced flap actuation. The gain scheduling also confirms the controller's effectiveness across the full operational velocity range. The complete simulation environment and controller are open-sourced.