Autonomous monopile inspection in a turbulent wake

Frequent underwater inspections are required to ensure the integrity of offshore infrastructure. These inspections currently rely on large vessels, Remotely Operated Vehicles (ROVs), and divers, making them dangerous, costly as well as labour- and emission-intensive. Autonomous Underwater Vehicles (AUVs) offer a more efficient approach to carry out these tasks. However, the AUVs are subjected to harsh environmental conditions and turbulent flows, which degrade the tracking performance to such an extent that the inspection sensors cannot provide adequate measurements.
This study investigates whether information from a previous circumnavigation around a monopile can improve the tracking performance during subsequent passes. This is tested for a monopile in a 0.5 m/s current, which results in a turbulent wake on the leeward side. A Repetitive Control approach has been employed for this purpose.
The tracking error was significantly reduced with this approach. The error in the distance the camera perceives decreased from 0.46 m to one centimetre, and the heading maximum absolute error improved from 21° to 1°, which shows that previous information can indeed be used to improve the behaviour. The remaining errors are attributed to the stochastic nature of the turbulence. The next step is to improve the sensor and thruster modelling, which was not included in this study.