Advanced perception, navigation and planning for autonomous in-water ship hull inspection

TLDR

Inspection of ship hulls and marine structures with autonomous underwater vehicles is a unique and challenging robotics application, raising complex design, perception, navigation, and planning questions due to acoustic constraints, poor water quality, and intricate structures. The paper develops and applies algorithms to address the central navigation and planning challenges on ship hulls. The authors implement two algorithmic classes: for open hulls they integrate acoustic and visual mapping to enable closed‑loop control relative to weld‑lines and biofouling, while for complex shafting, propeller, and rudder regions they deploy large‑scale planning routines to achieve high‑resolution full imaging coverage. The approaches were demonstrated in recent operations on naval ships.

Abstract

Inspection of ship hulls and marine structures using autonomous underwater vehicles has emerged as a unique and challenging application of robotics. The problem poses rich questions in physical design and operation, perception and navigation, and planning, driven by difficulties arising from the acoustic environment, poor water quality and the highly complex structures to be inspected. In this paper, we develop and apply algorithms for the central navigation and planning problems on ship hulls. These divide into two classes, suitable for the open, forward parts of a typical monohull, and for the complex areas around the shafting, propellers and rudders. On the open hull, we have integrated acoustic and visual mapping processes to achieve closed-loop control relative to features such as weld-lines and biofouling. In the complex area, we implemented new large-scale planning routines so as to achieve full imaging coverage of all the structures, at a high resolution. We demonstrate our approaches in recent operations on naval ships.