We present DexUMI - a data collection and policy learning framework that uses the human hand as the natural interface to transfer dexterous manipulation skills to various robot hands. DexUMI includes hardware and software adaptations to minimize the embodiment gap between the human hand and various robot hands. The hardware adaptation bridges the kinematics gap using a wearable hand exoskeleton. It allows direct haptic feedback in manipulation data collection and adapts human motion to feasible robot hand motion. The software adaptation bridges the visual gap by replacing the human hand in video data with high-fidelity robot hand inpainting. We demonstrate DexUMI's capabilities through comprehensive real-world experiments on two different dexterous robot hand hardware platforms, achieving an average task success rate of 86%.
TypeTele: Releasing Dexterity in Teleoperation by Dexterous Manipulation Types
School of Computer Science and Engineering, Sun Yat-sen University, China（中山大学计算机科学与工程学院）；Stanford University, USA（斯坦福大学）；Imperial College London, UK（伦敦帝国理工学院）
DexJoCo: A Benchmark and Toolkit for Task-Oriented Dexterous Manipulation on MuJoCo
NLPR & MAIS, CASIA（中国科学院南京自动化研究所与模式识别与人工智能实验室）；SJTU（上海交通大学）；MBZUAI（马克斯·普朗克研究所）；Beijing Institute of Basic Medical Sciences（北京基础医学研究所）；PKU & Galbot（北京大学与Galbot）；CUHK（香港大学）
EaDex: A Cross-Embodiment Dexterous Manipulation Framework from Low-Cost Demonstrations
Faculty of Robot Science and Engineering, Northeastern University（机器人科学与工程学院，东北大学）；Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences（深圳先进技术研究所，中国科学院）；School of Automation, Nanjing University of Information Science and Technology（自动化学院，南京信息科学技术大学）
A Dexterous and Compliant Gripper With Soft Hydraulic Actuation for Microgravity Manipulation
Aerospace Engineering Program, University of California, Berkeley（加州大学伯克利分校航空航天工程系）；Department of Mechanical Engineering, University of California, Berkeley（加州大学伯克利分校机械工程系）；Department of Mechanical Engineering, National University of Singapore（新加坡国立大学机械工程系）
FoLD: Force-Informed Learning for Dexterous Articulated Object Manipulation
University of Science and Technology of China（中国科学技术大学）；Institute of AI for Industries, Chinese Academy of Sciences（中国科学院人工智能产业研究院）；Shenzhen University（深圳大学）
