PUB - Publikationen an der Universität Bielefeld

The ability to manipulate deformable objects, such as textiles or paper, is a major prerequisite to bringing the capabilities of articulated robot hands closer to the level of manual intelligence that is the basis of most of our manual skills. We concentrate on the manipulation of paper, which affords us a rich interaction domain that has at yet not been solved for anthropomorphic robot hands. A key ability for this domain is the robust tracking and modelling of paper under conditions of occlusion and strong deformation. We present a marker based framework that realizes these properties robustly and in real-time. We compare a purely mathematical representation of a 2D paper manifold in 3D space with a soft-body-physics paper model and demonstrate the use of our visual tracking method to facilitate the coordination of two anthropomorphic 24 DOF Shadow Dexterous Hands while they grasp a flat-lying piece of paper using a combination of visually guided bulging and pinching.