10 papers
Web2Grasp: Learning Functional Grasps from Web Images of Hand-Object Interactions
Hongyi Chen, Yunchao Yao, Yufei Ye +8
Functional grasping is essential for enabling dexterous multi-finger robot hands to manipulate objects effectively. Prior work largely focuses on power grasps, which only involve h…
FingerEye: Learning Dexterous Manipulation with Continuous Vision-Tactile Sensing
Zhixuan Xu, Yichen Li, Xuanye Wu +2
Dexterous robotic manipulation requires perception that remains informative from pre-contact approach to contact initiation and post-contact control. We introduce FingerEye, a sens…
ContactExplorer: Contact Coverage-Guided Exploration for General-Purpose Dexterous Manipulation
Zixuan Liu, Ruoyi Qiao, Chenrui Tie +5
Reinforcement learning has achieved remarkable success in domains such as Atari games, navigation, and locomotion, where exploration can often be guided by novelty over states or d…
AdaClearGrasp: Learning Adaptive Clearing for Zero-Shot Robust Dexterous Grasping in Densely Cluttered Environments
Zixuan Chen, Wenquan Zhang, Jing Fang +7
In densely cluttered environments, physical interference, visual occlusions, and unstable contacts often cause direct dexterous grasping to fail, while aggressive singulation strat…
DexSinGrasp: Learning a Unified Policy for Dexterous Object Singulation and Grasping in Densely Cluttered Environments
Lixin Xu, Zixuan Liu, Zhewei Gui +6
Grasping objects in cluttered environments remains a fundamental yet challenging problem in robotic manipulation. While prior works have explored learning-based synergies between p…
T(R,O) Grasp: Efficient Graph Diffusion of Robot-Object Spatial Transformation for Cross-Embodiment Dexterous Grasping
Xin Fei, Zhixuan Xu, Huaicong Fang +2
Dexterous grasping remains a central challenge in robotics due to the complexity of its high-dimensional state and action space. We introduce T(R,O) Grasp, a diffusion-based framew…