In this paper a feature based single camera vision system for the safe landing of
an unmanned aerial vehicle (UAV) is proposed. The autonomous helicopter used
for tests is required to navigate from an initial to a final position in a partially
known environment, to locate a landing area and to land on it.
The algorithm proposed for the detection of safe landing areas is based on the
analysis of optical flow and of mutual geometric position of different kinds of
features, observed from different points of view .
Vision allows estimating the position and velocity of a set of features with
respect to the helicopter while the onboard, hierarchical, behavior-based
control system autonomously guides the helicopter.
Results, obtained using real data and a real helicopter in a outdoor scenario,
show the appropriateness of the vision-based approach. It does not require
any artificial landmark (e.g., helipad), is able to estimate correctly and
autonomously safe landing areas and is quite robust to occlusions.
