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

Takehiko Ohkawa, Jumpei Arima, Yuki Noguchi, Masatoshi Tateno, Makoto Sugiura, Takuya Okubo, Yuki Wakayama, Naoaki Kanazawa, Tatsuya Matsushima, Yohishiro Okumatsu, Kei Ota

Keywords: UMI, Manipulation, Dataset

Abstract: We introduce Yielding Universal Bidigital Interface (YUBI), a finger-aligned gripper designed to enable intuitive, ergonomic, and scalable data curation for bimanual dexterous manipulation. While handheld data collection systems such as Universal Manipulation Interface (UMI) have lowered the barrier for in-the-wild data collection, their bulky pistol-grip designs can present ergonomic and usability challenges for fine-grained, dexterous manipulation tasks. To address this limitation, YUBI presents a distinct design principle: yielding, finger-driven actuation that directly maps human finger movements to gripper jaw motion, allowing the jaws to naturally follow the operator's grip. This intuitive interface bridges the gap between human intent and robotic execution, facilitating more precise fingertip motor control. Furthermore, by integrating VR-based 6 DoF tracking into a rig-based operation setup, our system produces accurate gripper trajectories suitable for large-scale, high-quality data acquisition in tabletop scenarios. Leveraging this capability, we curate an unprecedented UMI-based dataset for bimanual dexterous manipulation, comprising 2730 hours of data across 300K episodes and 40 distinct tasks. Our experiments demonstrate that YUBI offers advantages over the original UMI gripper in versatility for complex bimanual tasks, dexterity, and operational efficiency. YUBI delivers an end-to-end framework spanning ergonomic gripper design and large-scale dataset curation, which advances research on robotic foundation models.

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Submission Number: 7