6 citations · 14 across the 5 of their papers we have counts for
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cs.RO2021★ 6 cited
RGB Matters: Learning 7-DoF Grasp Poses on Monocular RGBD Images
Minghao Gou, Hao-Shu Fang, Zhanda Zhu +3
General object grasping is an important yet unsolved problem in the field of robotics. Most of the current methods either generate grasp poses with few DoF that fail to cover most…
cs.RO2021
SuctionNet-1Billion: A Large-Scale Benchmark for Suction Grasping
Hanwen Cao, Hao-Shu Fang, Wenhai Liu +1
Suction is an important solution for the longstanding robotic grasping problem. Compared with other kinds of grasping, suction grasping is easier to represent and often more reliab…
cs.RO2020★ 3 cited
Transferable Active Grasping and Real Embodied Dataset
Xiangyu Chen, Zelin Ye, Jiankai Sun +4
Grasping in cluttered scenes is challenging for robot vision systems, as detection accuracy can be hindered by partial occlusion of objects. We adopt a reinforcement learning (RL)…