On-board real-time pose estimation for UAVs using deformable visual contour registration

We present a real time algorithm for estimating the pose of non-planar objects on which we have placed a visual marker. It is designed to overcome the limitations of small aerial robots, such as slow CPUs, low image resolution and geometric distortions produced by wide angle lenses or viewpoint changes. The method initially registers the shape of a known marker to the contours extracted in an image. For this purpose, and in contrast to state-of-the art, we do not seek to match textured patches or points of interest. Instead, we optimize a geometric alignment cost computed directly from raw polygonal representations of the observed regions using very simple and efficient clipping algorithms. Further speed is achieved by performing the optimization in the polygon representation space, avoiding the need of 2D image processing operations. Deformation modes are easily included in the optimization scheme, allowing an accurate registration of different markers attached to curved surfaces using a single deformable prototype. Once this initial registration is solved, the object pose is retrieved using a standard PnP approach. As a result, the method achieves accurate object pose estimation in real-time, which is very important for interactive UAV tasks, for example for short distance surveillance or bar assembly. We present experiments where our method yields, at about 30Hz, an average error of less than 5mm in estimating the position of a 19×19mm marker placed at 0.7m of the camera.