From the 2 of 6 linked papers with an AI index.
6 papers
UniCross: Unified Cross-Skill Dexterous Manipulation Synthesis
Hui Zhang, Julian Ferchow, Jie Song +1
The paper introduces a unified framework that models four fundamental dexterous manipulation skills—grasping, relocation, in‑hand rotation, and in‑hand translation—within a single…
PAKE: Learning Whole-Body Loco-Manipulation with Partial Kinematic Embeddings
Zhengmao He, Moonkyu Jung, Hyeongjun Kim +4
The paper introduces a hierarchical whole-body control framework for quadrupedal robots with a 6‑DoF arm, using a Kinematic Normalizing Flow to generate partial reference motions a…
FTP-1: A Generalist Foundation Tactile Policy Across Tactile Sensors for Contact-Rich Manipulation
Chengbo Yuan, Zicheng Zhang, Mingjie Zhou +14
Despite the success of vision-based generalist robotic policies, existing tactile-based policies remain tied to fixed embodiments and sensor setups. This is because tactile signals…
Learning Generalizable Hand-Object Tracking from Synthetic Demonstrations
Yinhuai Wang, Runyi Yu, Hok Wai Tsui +9
We present a system for learning generalizable hand-object tracking controllers purely from synthetic data, without requiring any human demonstrations. Our approach makes two key c…
RobustDexGrasp: Robust Dexterous Grasping of General Objects
Hui Zhang, Zijian Wu, Linyi Huang +2
The ability to robustly grasp a variety of objects is essential for dexterous robots. In this paper, we present a framework for zero-shot dynamic dexterous grasping using single-vi…
FunGrasp: Functional Grasping for Diverse Dexterous Hands
Linyi Huang, Hui Zhang, Zijian Wu +2
Functional grasping is essential for humans to perform specific tasks, such as grasping scissors by the finger holes to cut materials or by the blade to safely hand them over. Enab…