16 papers
Towards Human-level Dexterous Teleoperation
Puhao Li, Zeyuan Chen, Yingying Wu +9
The paper presents TeleDexter, a hand‑object co‑tracking controller that learns to map human teleoperation intent into low‑level contact actions for dexterous robot hands, achievin…
AetheRock: An Arm-Worn Robot Teaching System for Force-Guided Vision-Tactile Learning
Hong Li, Yue Xu, Yihan Tang +8
Force and tactile sensing are indispensable in contact-rich manipulation. However, force-aware robot learning faces critical challenges due to the incompatible assembly of tactile…
EgoGuide: Egocentric Guidance for Efficient Robot-Free Demonstration Collection and Learning
Yue Xu, Mingtao Nie, Tianle Li +4
Robot learning from real-world demonstrations is currently constrained by data scaling. Universal Manipulation Interface (UMI) provides an efficient robot-free data collection inte…
OmniClone: Engineering a Robust, All-Rounder Whole-Body Humanoid Teleoperation System
Yixuan Li, Le Ma, Yutang Lin +8
Whole-body humanoid teleoperation enables humans to remotely control humanoid robots, serving as both a real-time operational tool and a scalable engine for collecting demonstratio…
LessMimic: Long-Horizon Humanoid Interaction with Unified Distance Field Representations
Yutang Lin, Jieming Cui, Yixuan Li +3
Humanoid robots that autonomously interact with physical environments over extended horizons represent a central goal of embodied intelligence. Existing approaches rely on referenc…
Simultaneous Tactile-Visual Perception for Learning Multimodal Robot Manipulation
Yuyang Li, Yinghan Chen, Zihang Zhao +4
Robotic manipulation requires both rich multimodal perception and effective learning frameworks to handle complex real-world tasks. See-through-skin (STS) sensors, which combine ta…