DATASET FACET · FORMAT
HDF5 datasets for physical AI
Hierarchical data format commonly used for trajectories, demonstrations, and arrays.
DIRECT ANSWER
HDF5 pages collect datasets where this formatis materially relevant, then add truelabel’s commercial use, consent risk, and deployment fit notes so buyers can decide whether public data is enough.
MATCHED DATASETS
17 catalog entries
17 of 17 datasets
Open X-Embodiment
Published May 2026 · custom
A large cross-institution collection of robot demonstrations spanning many embodiments and manipulation tasks.
- Multi-institution robot demonstration corpus; exact per-task scale varies by contributing dataset.
- Commercial use unclear
- Best for: robot foundation model pretraining
DROID
Published May 2026 · custom
A real-world robot manipulation dataset focused on diverse teleoperated demonstrations outside narrow lab-only settings.
- Large real-world manipulation corpus; check source for current release counts.
- Commercial use unclear
- Best for: real-world manipulation pretraining
BridgeData V2
Published May 2026 · custom
A robot manipulation dataset from Berkeley focused on real-world behavior cloning and task generalization.
- Robot manipulation demonstrations across multiple tasks; source release describes exact split.
- Commercial use unclear
- Best for: behavior cloning
RT-1
Published May 2026 · custom
A robotics transformer data release associated with language-conditioned robot manipulation research.
- Large language-conditioned robot demonstrations described in the source paper and project materials.
- Commercial use unclear
- Best for: language-conditioned robotics
ALOHA
Published May 2026 · custom
A low-cost bimanual teleoperation platform and dataset family used for imitation learning in dexterous manipulation.
- Task-specific demonstrations released around the ALOHA platform and follow-on projects.
- Commercial use unclear
- Best for: bimanual imitation learning
RoboMimic
Published May 2026 · mit
A benchmark and dataset framework for robot imitation learning with standardized tasks and evaluation utilities.
- Benchmark datasets and demonstration formats vary by task suite.
- Source appears permissive; verify data terms
- Best for: imitation-learning baselines
RoboNet
Published May 2026 · custom
A multi-robot dataset for visual foresight and manipulation policy research.
- Multi-robot manipulation dataset; source materials specify exact robot/task counts.
- Commercial use unclear
- Best for: visual dynamics
CALVIN
Published May 2026 · custom
A benchmark for language-conditioned long-horizon robot manipulation in simulated environments.
- Long-horizon simulated benchmark and demonstrations.
- Commercial use unclear
- Best for: language-conditioned policy evaluation
BC-Z
Published May 2026 · custom
A behavior cloning project focused on zero-shot task generalization for robots.
- Task demonstrations and model references associated with the BC-Z project.
- Commercial use unclear
- Best for: behavior cloning
RoboSuite
Published May 2026 · mit
A simulation framework and benchmark suite for robot manipulation tasks.
- Simulation tasks and assets for manipulation research.
- Source appears permissive; verify data terms
- Best for: robot manipulation simulation
RH20T
Published May 2026 · custom
A real-world contact-rich robot manipulation dataset with multimodal sensing, force, audio, and human demonstration video.
- Source describes more than 110,000 contact-rich manipulation sequences with visual, force, audio, action, and human demonstration signals.
- Commercial use unclear
- Best for: contact-rich manipulation
AgiBot World
Published May 2026 · custom
A large-scale real-world robot manipulation dataset family for fine-grained manipulation, tool use, and multi-robot collaboration.
- Hugging Face organization page describes the Beta release as 1M+ trajectories and 2,976.4 hours across 217 tasks, 87 skills, 3,000+ objects, and 100+ real-world scenarios.
- Commercial use unclear
- Best for: large-scale manipulation pretraining
RoboCasa
Published May 2026 · custom
A large-scale kitchen simulation framework and dataset family for everyday manipulation tasks in diverse household environments.
- RoboCasa365 source materials describe 365 everyday tasks, 2,500 kitchen environments, 600+ hours of human demonstration data, and 1,600+ hours of synthetic demonstrations.
- Commercial use unclear
- Best for: large-scale kitchen simulation
LIBERO
Published May 2026 · custom
A benchmark suite for lifelong robot learning and language-conditioned manipulation tasks.
- Benchmark datasets are organized around multiple LIBERO task suites, including spatial, object, goal, and long-horizon manipulation variants.
- Commercial use unclear
- Best for: VLA benchmark evaluation
RoboSet
Published May 2026 · custom
A real-world multi-task kitchen manipulation dataset with teleoperated and kinesthetic demonstrations.
- Source describes 30,050 trajectories, including 9,500 collected through teleoperation, across 12 skills and 38 tasks with four camera views.
- Commercial use unclear
- Best for: real-world kitchen manipulation
RoboTurk
Published May 2026 · custom
A large-scale teleoperation data collection platform and dataset family for robot manipulation tasks.
- Project materials describe over 100 hours of real robot data and thousands of successful manipulation demonstrations collected through remote users.
- Commercial use unclear
- Best for: teleoperation collection design
UMI
Published May 2026 · custom
Universal Manipulation Interface is an in-the-wild human demonstration framework for transferring portable gripper data to robot policies.
- Project materials emphasize portable in-the-wild data collection and fast demonstrations for tasks such as cup manipulation, dish washing, cloth folding, and dynamic tossing.
- Commercial use unclear
- Best for: portable in-the-wild demonstrations
READ THE TAG WITH CARE
Do not treat this tag as the whole sourcing decision
Facet groupings are discovery aids, not final recommendations. A shared modality, task, robot, format, license, or commercial-use label only says that datasets are worth comparing; it does not prove that the source is safe, complete, or useful for a target model.
Use this grouping to shortlist candidates, then open the dataset profiles, run fit and license checks, and compare sources against the buyer's target environment. Thin tag results become useful only when they route the reader into deeper evidence and action surfaces.
The external references below keep the facet grounded in robotics data practice. They help reviewers understand why format, embodiment, trajectory quality, licensing, and real-world coverage matter before a team commits engineering time to ingestion.
When a facet has only a few matching datasets, treat that as a signal rather than a weakness. It may mean the public corpus is thin for that robot, task, or format, and the next move is a custom supplement with the facet written into acceptance criteria.
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
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