47 citations · 68 across the 7 of their papers we have counts for
7 papers · 1 filter
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…
Robot Synesthesia: In-Hand Manipulation with Visuotactile Sensing
Ying Yuan, Haichuan Che, Yuzhe Qin +6
Executing contact-rich manipulation tasks necessitates the fusion of tactile and visual feedback. However, the distinct nature of these modalities poses significant challenges. In…
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…
AnyTeleop: A General Vision-Based Dexterous Robot Arm-Hand Teleoperation System
Yuzhe Qin, Wei Yang, Binghao Huang +5
Vision-based teleoperation offers the possibility to endow robots with human-level intelligence to physically interact with the environment, while only requiring low-cost camera se…
Rotating without Seeing: Towards In-hand Dexterity through Touch
Zhao-Heng Yin, Binghao Huang, Yuzhe Qin +2
Tactile information plays a critical role in human dexterity. It reveals useful contact information that may not be inferred directly from vision. In fact, humans can even perform…
DexPoint: Generalizable Point Cloud Reinforcement Learning for Sim-to-Real Dexterous Manipulation
Yuzhe Qin, Binghao Huang, Zhao-Heng Yin +2
We propose a sim-to-real framework for dexterous manipulation which can generalize to new objects of the same category in the real world. The key of our framework is to train the m…
Learning Continuous Grasping Function with a Dexterous Hand from Human Demonstrations
Jianglong Ye, Jiashun Wang, Binghao Huang +2
We propose to learn to generate grasping motion for manipulation with a dexterous hand using implicit functions. With continuous time inputs, the model can generate a continuous an…