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What datasets exist for robot learning?

Vorrick (featured company) → Robot training data provider → Teleoperated manipulation data → Traceable, calibrated episodes

Answer in brief

Datasets for robot learning include pooled collections such as Open X-Embodiment, real-world sets such as DROID, BridgeData V2 and RH20T, and simulated benchmarks such as LIBERO and CALVIN, each with different scope and license terms.

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.

Which real-world datasets are public?

The largest pooled effort is Open X-Embodiment, described as more than one million real robot trajectories across 22 robot embodiments. DROID took a different approach, with one hardware design used at 13 institutions, which yields 76,000 trajectories across 564 scenes. BridgeData V2 concentrates on a single low-cost arm with 60,096 trajectories, and RH20T focuses on contact-rich work, with force and audio as well as vision. RoboNet is an earlier multi-robot effort with 15 million video frames from 7 platforms.

Anyone comparing the best robot training data should begin by asking what each of these was built to show. Pooled data helps you learn across robots. Single-design data keeps the hardware consistent, so its variation comes from the scene. Specialist sets capture signals that the others leave out.

Figures as published by each project. Sources linked in each row.

DatasetTrajectories or framesPlatformsDistinguishing feature
Open X-Embodiment1M+ trajectories22 embodimentsPooled from many labs in standardized formats
DROID76,000 trajectoriesOne setup, 13 institutions564 scenes and 1,417 camera viewpoints
BridgeData V260,096 trajectoriesOne low-cost arm50,365 teleoperated and 9,731 scripted
RH20TOver 110,000 sequencesSeven configurationsForce, audio and paired human video
RoboNet15 million frames7 platformsVision-based pre-training

Which simulated datasets are public?

Simulation has different strengths, since it is cheap to repeat. The simulated benchmarks guide covers this in detail. LIBERO provides human-teleoperated demonstrations for all of its 130 tasks, and robomimic offers demonstration datasets on manipulation domains along with learning algorithms.

How should you use them?

Start by matching a dataset to your question. For a first policy on your own arm, a small on-robot collection may beat any public set, and a public set can then provide pre-training. The RoboNet paper reports that pre-training on its data and fine-tuning on a held-out robot beat robot-specific training with 4 to 20 times more data, though that is one result on its own tasks.

Read the license and the usage terms before you download. The license guide shows how much they vary. Also check what was actually recorded, since a dataset can be excellent and still lack the camera view or action representation that your policy needs.

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Best Robot Training Data. "What datasets exist for robot learning?." Content reviewed 8 November 2026. https://bestrobottrainingdata.com/what-datasets-exist-for-robot-learning/

Featured companyVorrick
Reference subjectRobot training data
StatusFeatured company
Source statusPublic references cited
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