D(R,O) Grasp
NUS / SJTU research team
A shared representation of robot–object geometry for predicting grasps across different robotic hands.
What you can explore
Inspect the hand descriptions, point-cloud inputs and grasp validation used for cross-hand learning.
Before you use it
The documented evaluation depends on Isaac Gym and downloaded checkpoints and data. Generalization claims apply to the authors’ tested embodiments, not every hand in this catalog.
Original contributors
Zhenyu Wei, Zhixuan Xu, Jingxiang Guo, Yiwen Hou, Chongkai Gao, Zhehao Cai, Jiayu Luo and Lin Shao
License / access: Code: MIT · upstream data and robot assets have separate terms
Editorial reference · checked 2026-09-22