Grabette: an open system to record robot-manipulation data
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Key Takeaways
- The bottleneck isn't the model.
- That is difficult to scale with the wide variety of tasks and environnements required.
- And that's the bigger goal: if recording a demonstration is as easy as shooting a video, anyone can contribute.
We want Grabette to seed a large, open, collaborative manipulation dataset .
- Grabette is something anyone can build on a workbench, use in the field, and contribute data from.
Meet Grabette We have been developing Grabette for months, and we feel it has become usable enough to share.
- So, meet Gripette , the robotic arm end-effector twin of Grabette.
The bottleneck isn't the model. Robot learning has a supply problem. We have capable policy architectures (transformer-based VLAs, diffusion and flow-matching policies, and even world models) and the GPUs to train them.
What we lack is large, diverse, real-world manipulation data. Teleoperating a robot to collect it can be expensive and demanding: first of all, it requires a robot . And depending on the teleoperation method, data collection can be tedious for the user if it takes hours and involve significant hardware and logistical challenges.
That is difficult to scale with the wide variety of tasks and environnements required. But you don't need a robot to collect robot data. Just a human hand, a gripper, a camera, and a way to recover the 6-DoF trajectory of what the hand did.
For more details please read the original article at Hugging Face.
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