Records
11
HF AUTHOR CLUSTER
oxe-auge robotics datasets
11 robotics-tagged HF records from oxe-auge, totaling 4,081 cumulative downloads. Some records cite published arxiv research.
DIRECT ANSWER
Author clusters consolidate every record from one publisher into a single buyer-review surface. oxe-auge ships 11 robotics datasets on Hugging Face. Top license: cc-by-4.0. Of those, 11 get a full standalone page, 0 get a shorter profile, and 0 are folded into this cluster.
Cumulative downloads
4,081
Top license
cc-by-4.0
DATASETS
All 11 robotics records from oxe-auge
11 of 11 datasets
bridge_train_0_5000_augmented
Published Nov 2025 · cc-by-4.0 · oxe-auge
bridge_train_0_5000_augmented Overview Codebase version: v3.0 Robots: google_robot, images, jaco, kinova3, kuka_iiwa, panda, sawyer, ur5e, xarm7 FPS: 5 Episodes: 5,000 Frames: 170,417 Splits: train: 0:5000 Data Layout data_path :…
- 555 downloads
- 100K<n<1M
- Paper available
bridge_train_20000_25460_augmented
Published Nov 2025 · cc-by-4.0 · oxe-auge
bridge_train_20000_25460_augmented Overview Codebase version: v3.0 Robots: google_robot, images, jaco, kinova3, kuka_iiwa, panda, sawyer, ur5e, xarm7 FPS: 5 Episodes: 5,460 Frames: 185,428 Splits: train: 0:5460 Data Layout data_path :…
- 404 downloads
- 100K<n<1M
- Paper available
berkeley_autolab_ur5_train_400_500_augmented
Published Oct 2025 · cc-by-4.0 · oxe-auge
berkeley_autolab_ur5_train_400_500 Overview Codebase version: v2.1 Robots: google_robot, images, jaco, kinova3, kuka_iiwa, panda, sawyer, widowX, xarm7 FPS: 5.0 Episodes: 100 Frames: 9,479 Videos: 900 Chunks: 1 Splits: train: 0:100 Data…
- 369 downloads
- 1K<n<10K
iamlab_cmu_pickup_insert_train_500_631_augmented
Published Nov 2025 · cc-by-4.0 · oxe-auge
iamlab_cmu_pickup_insert_train_500_631_augmented Overview Codebase version: v2.1 Robots: google_robot, images, jaco, kinova3, kuka_iiwa, sawyer, ur5e, widowX, xarm7 FPS: 20.0 Episodes: 131 Frames: 30,143 Videos: 1,179 Chunks: 1 Splits:…
- 357 downloads
- 10K<n<100K
berkeley_autolab_ur5_train_300_400_augmented
Published Oct 2025 · cc-by-4.0 · oxe-auge
berkeley_autolab_ur5_train_300_400 Overview Codebase version: v2.1 Robots: google_robot, images, jaco, kinova3, kuka_iiwa, panda, sawyer, widowX, xarm7 FPS: 5.0 Episodes: 100 Frames: 9,934 Videos: 900 Chunks: 1 Splits: train: 0:100 Data…
- 355 downloads
- 1K<n<10K
bridge_test_0_3475_augmented
Published Nov 2025 · cc-by-4.0 · oxe-auge
bridge_test_0_3475_augmented Overview Codebase version: v3.0 Robots: google_robot, images, jaco, kinova3, kuka_iiwa, panda, sawyer, ur5e, xarm7 FPS: 5 Episodes: 3,475 Frames: 118,603 Splits: train: 0:3475 Data Layout data_path :…
- 354 downloads
- 100K<n<1M
- Paper available
bridge_train_15000_20000_augmented
Published Nov 2025 · cc-by-4.0 · oxe-auge
bridge_train_15000_20000_augmented Overview Codebase version: v3.0 Robots: google_robot, images, jaco, kinova3, kuka_iiwa, panda, sawyer, ur5e, xarm7 FPS: 5 Episodes: 5,000 Frames: 169,127 Splits: train: 0:5000 Data Layout data_path :…
- 351 downloads
- 100K<n<1M
- Paper available
bridge_train_5000_10000_augmented
Published Nov 2025 · cc-by-4.0 · oxe-auge
bridge_train_5000_10000_augmented Overview Codebase version: v3.0 Robots: google_robot, images, jaco, kinova3, kuka_iiwa, panda, sawyer, ur5e, xarm7 FPS: 5 Episodes: 5,000 Frames: 168,737 Splits: train: 0:5000 Data Layout data_path :…
- 350 downloads
- 100K<n<1M
- Paper available
bridge_train_10000_15000_augmented
Published Nov 2025 · cc-by-4.0 · oxe-auge
bridge_train_10000_15000_augmented Overview Codebase version: v3.0 Robots: google_robot, images, jaco, kinova3, kuka_iiwa, panda, sawyer, ur5e, xarm7 FPS: 5 Episodes: 5,000 Frames: 170,583 Splits: train: 0:5000 Data Layout data_path :…
- 335 downloads
- 100K<n<1M
- Paper available
berkeley_autolab_ur5_train_800_896_augmented
Published Oct 2025 · cc-by-4.0 · oxe-auge
berkeley_autolab_ur5_train_800_896 Overview Codebase version: v2.1 Robots: google_robot, images, jaco, kinova3, kuka_iiwa, panda, sawyer, widowX, xarm7 FPS: 5.0 Episodes: 96 Frames: 9,360 Videos: 864 Chunks: 1 Splits: train: 0:96 Data…
- 330 downloads
- 1K<n<10K
berkeley_autolab_ur5_train_0_100_augmented
Published Oct 2025 · cc-by-4.0 · oxe-auge
berkeley_autolab_ur5_train_0_100 Overview Codebase version: v2.1 Robots: google_robot, images, jaco, kinova3, kuka_iiwa, panda, sawyer, widowX, xarm7 FPS: 5.0 Episodes: 100 Frames: 9,863 Videos: 900 Chunks: 1 Splits: train: 0:100 Data…
- 321 downloads
- 1K<n<10K
KEEP DIGGING
Use this record as part of a broader dataset review
A dataset record is only useful when it connects into the rest of the buyer workflow. The next review step is usually not another summary; it is a fit check, rights triage, source comparison, or custom bounty spec that names the missing proof.
For physical AI teams, the hard question is whether the public source can support a specific model objective under real deployment constraints. That requires adjacent dataset records, tools, comparisons, and sourcing paths, plus external references that a reviewer can open and challenge.
Use the links below to keep the review grounded. Start broad when discovery is incomplete, move into profile and comparison pages when the candidate source is known, and switch to custom collection when the blocker is rights, consent, geography, robot embodiment, or target environment coverage.
Where to go next
- Physical AI dataset catalogUse the catalog to compare source-backed dataset profiles by modality, task, rights signal, consent risk, and deployment fit.
- Hugging Face robotics indexScan the broader robotics dataset surface before narrowing into promoted profiles, comparisons, and custom collection specs.
- Dataset changelogTrack source updates, licensing notes, and buyer-readiness changes that should trigger a renewed review.
- Dataset fit checkerScore whether a public source is enough for the model, rights path, modalities, and target environment.
- License risk checkerSeparate source license language from contributor consent, redistribution, private-space risk, and model-use assumptions.
- Data spec generatorTurn a public-source gap into a scoped capture request with sample QA, metadata, and delivery requirements.
- Vendor alternatives hubCompare data providers when the answer is not another public dataset but a better sourcing or capture route.
- Data annotation companiesUse the company index to separate annotation vendors, data engines, marketplaces, and specialist capture teams.
Other places to verify the claims
- Scale AI physical AI data engineMarket context for why physical AI systems need custom, enriched, real-world data beyond generic labeling workflows.
- LeRobot documentationRobotics dataset and tooling context for Hugging Face based collection, sharing, conversion, and training workflows.
- Open X-EmbodimentA cross-embodiment robotics dataset reference for comparing trajectory scale, robot diversity, and VLA training assumptions.
- DROID datasetA large in-the-wild robot manipulation dataset reference for real-world trajectory capture and deployment transfer risk.
TRUELABEL ROUTING
Need data like oxe-auge ships, but with cleaner rights?
If the Hub records don't carry the license, consent, or deployment fit your team needs, commission a custom collection on the same modality with explicit commercial terms.