  This work addresses the problem of coupling vision-based navigation systems
for Unmanned Aerial Vehicles (UAVs) with robust obstacle avoidance
capabilities. The former problem is solved by maximizing the visibility of the
points of interest, while the latter is modeled by means of ellipsoidal
repulsive areas. The whole problem is transcribed into an Optimal Control
Problem (OCP), and solved in a few milliseconds by leveraging state-of-the-art
numerical optimization. The resulting trajectories are well suited for reaching
the specified goal location while avoiding obstacles with a safety margin and
minimizing the probability of losing the route with the target of interest.
Combining this technique with a proper ellipsoid shaping (i.e., by augmenting
the shape proportionally with the obstacle velocity or with the obstacle
detection uncertainties) results in a robust obstacle avoidance behavior. We
validate our approach within extensive simulated experiments that show
effective capabilities to satisfy all the constraints even in challenging
conditions. We release with this paper the open source implementation.
