2 citations · 2 across the 2 of their papers we have counts for
7 papers
DexFlyWheel: A Scalable and Self-improving Data Generation Framework for Dexterous Manipulation
Kefei Zhu, Fengshuo Bai, YuanHao Xiang +8
Dexterous manipulation is critical for advancing robot capabilities in real-world applications, yet diverse and high-quality datasets remain scarce. Existing data collection method…
A Survey on Vision-Language-Action Models: An Action Tokenization Perspective
Yifan Zhong, Fengshuo Bai, Shaofei Cai +11
The remarkable advancements of vision and language foundation models in multimodal understanding, reasoning, and generation has sparked growing efforts to extend such intelligence…
ClutterDexGrasp: A Sim-to-Real System for General Dexterous Grasping in Cluttered Scenes
Zeyuan Chen, Qiyang Yan, Yuanpei Chen +6
Dexterous grasping in cluttered scenes presents significant challenges due to diverse object geometries, occlusions, and potential collisions. Existing methods primarily focus on s…
Communication-Efficient Desire Alignment for Embodied Agent-Human Adaptation
Yuanfei Wang, Xinju Huang, Fangwei Zhong +4
While embodied agents have made significant progress in performing complex physical tasks, real-world applications demand more than pure task execution. The agents must collaborate…
Dexterous Non-Prehensile Manipulation for Ungraspable Object via Extrinsic Dexterity
Yuhan Wang, Yu Li, Yaodong Yang +1
Objects with large base areas become ungraspable when they exceed the end-effector's maximum aperture. Existing approaches address this limitation through extrinsic dexterity, whic…
DexGraspVLA: A Vision-Language-Action Framework Towards General Dexterous Grasping
Yifan Zhong, Xuchuan Huang, Ruochong Li +9
Dexterous grasping remains a fundamental yet challenging problem in robotics. A general-purpose robot must be capable of grasping diverse objects in arbitrary scenarios. However, e…