Robotic Grasping through Combined Image-Based Grasp Proposal and 3D Reconstruction
Daniel Yang,Tarik Tosun,Benjamin Eisner,Volkan Isler,Daniel Lee,Daniel Yang,Tarik Tosun,Benjamin Eisner,Volkan Isler,Daniel Lee
We present a novel approach to robotic grasp planning using both a learned grasp proposal network and a learned 3D shape reconstruction network. Our system generates 6-DOF grasps from a single RGB-D image of the target object, which is provided as input to both networks. By using the geometric reconstruction to refine the candidate grasp produced by the grasp proposal network, our system is able t...
