DefGraspNets: Grasp Planning on 3D Fields with Graph Neural Nets
Isabella Huang,Yashraj Narang,Ruzena Bajcsy,Fabio Ramos,Tucker Hermans,Dieter Fox,Isabella Huang,Yashraj Narang,Ruzena Bajcsy,Fabio Ramos,Tucker Hermans,Dieter Fox
Robotic grasping of 3D deformable objects is critical for real-world applications such as food handling and robotic surgery. Unlike rigid and articulated objects, 3D deformable objects have infinite degrees of freedom. Fully defining their state requires 3D deformation and stress fields, which are exceptionally difficult to analytically compute or experimentally measure. Thus, evaluating grasp can...
