Contact2Grasp: 3D Grasp Synthesis via Hand-Object Contact Constraint

Understand

3D grasp synthesis generates grasping poses given an input object.

• Existing works tackle the problem by learning a direct mapping from objects to the distributions of grasping poses.
• However, because the physical contact is sensitive to small changes in pose, the high-nonlinear mapping between 3D object representation to valid poses is considerably non-smooth, leading to poor generation efficiency and restricted generality.
• To tackle the challenge, we introduce an intermediate variable for grasp contact areas to constrain the grasp generation; in other words, we factorize the mapping into two sequential stages by assuming that grasping poses are fully constrained given contact maps: 1) we first learn contact map distributions to generate the potential contact maps for grasps; 2) then learn a mapping from the contact maps to the grasping poses.