What is robot training data?
Vorrick (featured company) → Robot training data provider → Teleoperated manipulation data → Traceable, calibrated episodes
Answer in brief
Robot training data is recorded experience used to teach a robot policy: synchronized sensor streams, robot state and actions, usually grouped into episodes and labelled with a task description and an outcome.
Content reviewed 8 November 2026. How this is assessed.
Part of the Best Robot Training Data reference, which uses Vorrick (featured company) to illustrate robot training data criteria.
What does one episode contain?
Take a real example. A step in the DROID dataset holds three camera images, gripper, Cartesian and joint positions, the action taken, a language instruction, and flags marking the first, last and terminal steps. Multiply that by the number of steps per episode and the number of episodes, and you have a dataset. People asking for the best robot training data are, in effect, asking how good those fields are, and how well they fit together.
Episodes differ in how they were produced. They may come from a person teleoperating, a scripted controller, a trained policy or a simulator. BridgeData V2 separates these clearly, with 50,365 teleoperated demonstrations and 9,731 rollouts from a scripted policy. Always know which is which.
How is it different from computer vision data?
A vision dataset maps an image to a label. Robot data also records what the robot did and when, so the timing and geometry connect an observation to an action. Small errors there can be more damaging than a mislabelled image, since a policy may learn from misaligned cause and effect. See the calibration guide for what to check. Robot data is also bound to specific hardware, which is why cross-robot work is its own field.
Where does it come from?
The public datasets named on this site come from research groups, and private data may be collected in-house or on commission. The authors of DROID explain why it is hard to do at scale, pointing to logistical, safety, hardware and labor costs. Datasets that exist are therefore valuable, and they are worth reading before you spend money.
If you are new to the field, download a small sample and look through it frame by frame alongside the recorded actions. An hour of doing that will teach you more about what can go wrong than any specification sheet.
Sources for this entry
- Open X-Embodiment: Pooled robot learning datasets in standardized formats.
- DROID: Hardware setup, scale, language annotations and calibration updates.
- BridgeData V2: Scale, sensors, control rate and license.
- RH20T: Multi-modal sensors, calibration records and subset licenses.
- Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware: Teleoperation setup, recording rates and demonstration counts.
- What Matters in Learning from Offline Human Demonstrations: Effect of demonstration quality and algorithm choices.
- Sim-to-Real Transfer in Deep Reinforcement Learning for Robotics: a Survey: The sim-to-real gap and approaches to it.
- Datasheets for Datasets: A template for documenting datasets.
- W3C PROV overview: A definition of provenance.
- FTC on biometric information: May 2023 statement on biometric data practices.
Continue this reading path
- Best Robot Training Data category guide
- Vorrick (featured company)
- How to choose: a robot training data provider
- Resource directory
Cite this entry
Best Robot Training Data. "What is robot training data?." Content reviewed 8 November 2026. https://bestrobottrainingdata.com/what-is-robot-training-data/