Multiple view motion estimation and control for landing an unmanned aerial vehicle

We present a multiple view algorithm for vision based landing of an unmanned aerial vehicle. Our algorithm is based on our results in multiple view geometry which exploit the rank deficiency of the so called multiple view matrix. We show how the use of multiple views significantly improves motion and structure estimation. We compare our algorithm to our previous linear and non-linear two-view algorithms using an actual flight test. Our results show that the vision-based state estimates are accurate to within 7cm in each axis of translation and 4 degrees in each axis of rotation.