Vision-Based Autonomous Underwater Vehicle Navigation in Poor Visibility Conditions Using a Model-Free Robust Control

Abstract EN

This paper presents a vision-based navigation system for an autonomous underwater vehicle in semistructured environments with poor visibility.

In terrestrial and aerial applications, the use of visual systems mounted in robotic platforms as a control sensor feedback is commonplace.

However, robotic vision-based tasks for underwater applications are still not widely considered as the images captured in this type of environments tend to be blurred and/or color depleted.

To tackle this problem, we have adapted the l α β color space to identify features of interest in underwater images even in extreme visibility conditions.

To guarantee the stability of the vehicle at all times, a model-free robust control is used.

We have validated the performance of our visual navigation system in real environments showing the feasibility of our approach.