Class-Specific Grasping of 3D Objects from a Single 2D Image


H. -P. Chiu, Huan Liu, L. P. Kaelbling and T. Lozano-Pérez, “Class-specific grasping of 3D objects from a single 2D image,” 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010, pp. 579-585, doi: 10.1109/IROS.2010.5652597.


Our goal is to grasp 3D objects given a single image, by using prior 3D shape models of object classes. The shape models, defined as a collection of oriented primitive shapes centered at fixed 3D positions, can be learned from a few labeled images for each class. The 3D class model can then be used to estimate the 3D shape of a detected object, including occluded parts, from a single image. The estimated 3D shape is used as to select one of the target grasps for the object. We show that our 3D shape estimation is sufficiently accurate for a robot to successfully grasp the object, even in situations where the part to be grasped is not visible in the input image.

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