Introducing the second generation of Origami robot hands!
After 7 months of development, our team is excited to unveil what we've been working on, pushing the boundaries of robotic dexterity.
This is just the beginning. Stay tuned for more details on our new hands!
Launching project flow. Our new generation robot hand.
Direct drive, liquid cooling.
From now, the heating problem is solved for robot hands.
more soon… @origami_robo
We’re excited to announce our collaboration with @PalatialSim to build the Dexterity Factory, a real2sim2real pipeline designed to bring human dexterity to robot hands.
By combining Origami Robotics’ S1 skill-capture gloves and robot hands with Palatial’s simulation technology, we’re building a pipeline that connects real-world human demonstrations, simulation, and robotic manipulation.
This is a step toward scaling how robots learn to manipulate everyday objects.
And we’re just getting started.
Next week, we’ll release our first 100 open-source datasets to support the robotics research community.
What makes human demonstration data valuable for robot learning?
Meet S1, our skill capture glove, designed to capture precise joint movements, touch, and video together.
From complex dexterous tasks to tracking through occlusion, S1 is built to make high-quality human demonstration data scalable.
Read our blog: https://t.co/ZBVLUnk5Xm
A million hours of what?
If we’re scaling human demonstrations for robot learning, what should each hour contain?
We built S1, our skill capture glove, alongside our robot hand to record joint movements that map to robot targets, with touch and video on the same timeline.