A PFM-based control architecture for a visually guided underwater cable tracker to achieve navigation in troublesome scenarios

Abstract

Nowadays, the surveillance and inspection of underwater installations, such as power or telecommunication cables and pipelines, are carried out by trained operators who, from the surface, control a Remotely Operated Vehicle (ROV) with cameras mounted over it. This is a tedious, time-consuming and expensive task, prone to errors mainly because of loss of attention or fatigue of the operator and also due to the typical low quality of seabed images. In this study, a control architecture based on Potential Field Methods (PFM) for visually guiding an Autonomous Underwater Vehicle (AUV) to detect and track a cable, or pipeline, laid on the seabed is presented. Additionally, a solution to the typical trapping problem linked to this kind of control systems is proposed. The efficiency of the solution is evaluated and compared against other popular strategies appearing in the literature. A 3D simulation environment which incorporates the hydrodynamic model of a real underwater vehicle called GARBI has been used with this purpose.