YUBI (Yielding Universal Bidigital Interface), a research-oriented robotic interface developed by the #FrontierResearchCenter, will be showcased at the @airoa_jp booth (#ICRA2026 / Booth 073).
YUBI is designed for intuitive bimanual robot operation and scalable data collection. +
On June 5 at the #ICRA2026 Workshop “Beyond Teleoperation: Learning from Diverse Human and Simulation Data,” AIRoA (@airoa_jp) and the #FrontierResearchCenter will present:
“YUBI: Yielding Universal Bidigital Interface for Scalable Data Curation in Robotic Manipulation.” +
The April 2026 issue of Science #Robotics is out!
This month's cover highlights large behavior models that can outperform single-task policies at complex manipulation tasks like installing a bike rotor. Learn about this research and more: https://t.co/89AzyDYh0O
Awesome. As a long-time UMI fan myself, it's sometimes surprisingly hard to convince people that this is the way to go. And you need a full-stack team with this conviction to achieve what Sunday did. Hopefully more people will wake up now.
Instead of teleoperation, we train solely on data from our Skill Capture Glove.
The glove is co-designed with Memo's hand, meaning they share the exact same geometry and sensor suite.
If you can do it wearing the glove, Memo can learn it.
Massive dataset but egocentric video is not going to get us dexterous manipulation policies.
Egocentric data provides high-level semantic scene and task understanding (which frontier VLMs already generally provide). What is needed is fine sub-mm-level finger pose & force data.