most citedDynamic Handover: Throw and Catch with Bimanual Hands

6 citations · 12 across the 7 of their papers we have counts for

collaborators

7 papers

cs.RO20242 cited

Bunny-VisionPro: Real-Time Bimanual Dexterous Teleoperation for Imitation Learning

Runyu Ding, Yuzhe Qin, Jiyue Zhu +5

Teleoperation is a crucial tool for collecting human demonstrations, but controlling robots with bimanual dexterous hands remains a challenge. Existing teleoperation systems strugg…

cs.RO2024

Part-Guided 3D RL for Sim2Real Articulated Object Manipulation

Pengwei Xie, Rui Chen, Siang Chen +6

Manipulating unseen articulated objects through visual feedback is a critical but challenging task for real robots. Existing learning-based solutions mainly focus on visual afforda…

cs.RO2024

Sim2Real Manipulation on Unknown Objects with Tactile-based Reinforcement Learning

Entong Su, Chengzhe Jia, Yuzhe Qin +4

Using tactile sensors for manipulation remains one of the most challenging problems in robotics. At the heart of these challenges is generalization: How can we train a tactile-base…

cs.RO2024

CyberDemo: Augmenting Simulated Human Demonstration for Real-World Dexterous Manipulation

Jun Wang, Yuzhe Qin, Kaiming Kuang +4

We introduce CyberDemo, a novel approach to robotic imitation learning that leverages simulated human demonstrations for real-world tasks. By incorporating extensive data augmentat…

cs.RO20236 cited

Dynamic Handover: Throw and Catch with Bimanual Hands

Binghao Huang, Yuanpei Chen, Tianyu Wang +4

Humans throw and catch objects all the time. However, such a seemingly common skill introduces a lot of challenges for robots to achieve: The robots need to operate such dynamic ac…

cs.RO20232 cited

DexArt: Benchmarking Generalizable Dexterous Manipulation with Articulated Objects

Chen Bao, Helin Xu, Yuzhe Qin +1

To enable general-purpose robots, we will require the robot to operate daily articulated objects as humans do. Current robot manipulation has heavily relied on using a parallel gri…