Language-Table
Google's large language-conditioned tabletop block-manipulation dataset: ~442K real + ~181K sim xArm6 trajectories, plus a sim benchmark.
| Year | 2022 |
|---|---|
| Episodes | 442,226 |
| Total hours | 3,865 |
| Embodiments | xarm |
| Modalities | ee_pose, language, proprioception, rgb |
| Task categories | manipulation, language |
| License | Apache-2.0 |
| Access | open — commercial use permitted |
| Maintainer | Robotics at Google / Google Research |
Language-Table is a suite of human-collected datasets and a multi-task continuous control benchmark for open-vocabulary visuolinguomotor learning, released with the paper 'Interactive Language: Talking to Robots in Real Time'. It contains nearly 600,000 natural-language-labeled trajectories of a UFACTORY xArm6 robot moving colored blocks on a tabletop (442,226 real-robot episodes plus simulated human-controlled and oracle episodes). Observations are third-person RGB images (captured at 640x360, resized to 320x180) plus end-effector/block state, and the arm is constrained to a 2D plane and acts via a 2D Cartesian end-effector delta setpoint.