  Visual monitoring operations underwater require both observing the objects of
interest in close-proximity, and tracking the few feature-rich areas necessary
for state estimation.This paper introduces the first navigation framework,
called AquaVis, that produces on-line visibility-aware motion plans that enable
Autonomous Underwater Vehicles (AUVs) to track multiple visual objectives with
an arbitrary camera configuration in real-time. Using the proposed pipeline,
AUVs can efficiently move in 3D, reach their goals while avoiding obstacles
safely, and maximizing the visibility of multiple objectives along the path
within a specified proximity. The method is sufficiently fast to be executed in
real-time and is suitable for single or multiple camera configurations.
Experimental results show the significant improvement on tracking multiple
automatically-extracted points of interest, with low computational overhead and
fast re-planning times
