Communications in Information and Systems
Volume 18 (2018)
Robust shape estimation for 3D deformable object manipulation
Pages: 107 – 124
Existing shape estimation methods for deformable object manipulation suffer from the drawbacks of being off-line, model dependent, noise-sensitive or occlusion-sensitive, and thus are not appropriate for manipulation tasks requiring high precision. In this paper, we present a real-time shape estimation approach for autonomous robotic manipulation of 3D deformable objects. Our method fulfills all the requirements necessary for the high-quality deformable object manipulation in terms of being real-time, model-free and robust to noise and occlusion. These advantages are accomplished using a joint tracking and reconstruction framework, in which we track the object deformation by aligning a reference shape model with the stream input from the RGB-D camera, and simultaneously upgrade the reference shape model according to the newly captured RGB-D data. We have evaluated the quality and robustness of our real-time shape estimation pipeline on a set of deformable manipulation tasks implemented on physical robots.
This work was supported by the HKSAR Research Grants Council (RGC) General Research Fund (GRF) CityU 21203216, and by the NSFC/RGC Joint Research Scheme (CityU103/16-NSFC61631166002).
Published 17 October 2018