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

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. © 2016 ricardo pérez-alcocer et al.