SeaVis: Modeling and Control of a Remotely Operated Towed Vehicle for Seabed Visualization and Mapping

TL;DR

This paper presents a new mathematical model and a gain-scheduled LQR controller for a remotely operated towed vehicle, demonstrating improved robustness and efficiency in seabed mapping simulations.

Contribution

Introduction of a novel mathematical model and a gain-scheduled LQR controller for SeaVis ROTVs, validated through high-fidelity simulation benchmarks.

Findings

LQR outperforms PID in robustness and control efficiency.

Controller maintains effectiveness across full velocity range.

Simulation environment and controller are open-sourced.

Abstract

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.