arXiv 2606.102442026-06-08cs.ROcs.AI

YUBI：面向大规模双手灵巧操作的通用双指接口

YUBI: Yielding Universal Bidigital Interface for Bimanual Dexterous Manipulation at Scale

AI Robot Association (AIRoA)（AI机器人协会）；Toyota Motor Corporation（丰田汽车公司）；National Institute of Advanced Industrial Science and Technology (AIST)（国家先进工业科学与技术研究院）；The University of Tokyo（东京大学）；Institute of Science Tokyo（东京科学研究所）；Waseda University（早稻田大学）

Takehiko Ohkawa, Jumpei Arima, Yuki Noguchi, Masatoshi Tateno, Makoto Sugiura, Takuya Okubo, Kengo Ikeuchi, Yuma Shin, Hiroki Nishizawa, Naoaki Kanazawa, Yuki W… 展开作者

Takehiko Ohkawa, Jumpei Arima, Yuki Noguchi, Masatoshi Tateno, Makoto Sugiura, Takuya Okubo, Kengo Ikeuchi, Yuma Shin, Hiroki Nishizawa, Naoaki Kanazawa, Yuki Wakayama, Daiki Fukunaga, Koshi Makihara, Tomohiro Motoda, Floris Erich, Yukiyasu Domae, Tatsuya Matsushima, Yohishiro Okumatsu, Kei Ota

备注：: Project page: https://yubi.airoa.io/

阅读 PDF

arXiv 页面 ↗HTML 原文 ↗

AI总结：

提出YUBI手指对齐夹爪，通过屈服式手指驱动映射实现直观、符合人体工学的双手灵巧操作数据采集，构建8434小时/120万集/119任务数据集，单策略跨多机器人迁移。

摘要：

我们引入了Yielding Universal Bidigital Interface (YUBI)，一种手指对齐的夹爪，旨在实现双手灵巧操作的直观、符合人体工学且可扩展的数据采集。虽然手持数据采集系统（如Universal Manipulation Interface (UMI)）实现了低成本数据采集，但其笨重的手枪式握把设计可能给精细灵巧操作任务带来人体工学和使用性挑战。为此，YUBI提出了一种独特的设计原则：屈服式手指驱动，将人类手指运动直接映射到夹爪钳口运动。使用YUBI设备，我们建立了一个集成基于VR的6自由度夹爪跟踪的数据采集系统，确保高保真轨迹数据获取。我们整理了一个前所未有的基于UMI的数据集：8434小时，涵盖120万集和119个任务。实验表明，YUBI在复杂双手任务的通用性、灵巧性和操作效率方面优于UMI夹爪。通过在多个平台上安装夹爪，在YUBI数据集上训练的单一策略可迁移到多个双手机器人（UR、Franka和ELEY），证实采集的数据可直接作为策略监督执行。我们发布了夹爪硬件、数据采集软件和数据集作为集成堆栈，为开放社区提供可复现的大规模数据采集路径，以推动机器人基础模型的发展。

英文摘要：

We introduce Yielding Universal Bidigital Interface (YUBI), a finger-aligned gripper designed to enable intuitive, ergonomic, and scalable data collection for bimanual dexterous manipulation. While handheld data collection systems such as Universal Manipulation Interface (UMI) enable affordable data collection, their bulky pistol-grip designs can pose ergonomic and usability challenges for fine-grained, dexterous manipulation tasks. To address this, YUBI presents a distinct design principle: yielding, finger-driven actuation that directly maps human finger movements to gripper jaw motion. Using the YUBI devices, we set up a data collection system with integrated VR-based 6 DoF tracking of the gripper, ensuring high-fidelity trajectory data acquisition. We curate a UMI-based dataset of unprecedented scale: 8,434 hours across 1.20M episodes and 119 tasks. Experiments show that YUBI offers advantages over the UMI gripper in versatility for complex bimanual tasks, dexterity, and operational efficiency. A single policy trained on the YUBI dataset transfers across multiple bimanual robots (UR, Franka, and ELEY) simply by mounting the gripper on each platform, confirming that the collected data are directly executable as policy supervision. We release the gripper hardware, data-collection software, and dataset as one integrated stack, offering the open community a reproducible path to large-scale data acquisition for advancing robotic foundation models.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。