Physical AI dataset catalog
Use the catalog to compare source-backed dataset profiles by modality, task, rights signal, consent risk, and deployment fit.
DATASET FACET · ROBOT
Simulation datasets for physical AI
Synthetic robot environments used for scalable benchmark and policy development.
DIRECT ANSWER
Simulation pages collect datasets where this robotis 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
16 catalog entries
16 of 16 datasets
RT-1
Commercial use unclear · Large language-conditioned robot demonstrations described in the source paper and project materials.
A robotics transformer data release associated with language-conditioned robot manipulation research.
RoboMimic
Source appears permissive; verify data terms · Benchmark datasets and demonstration formats vary by task suite.
A benchmark and dataset framework for robot imitation learning with standardized tasks and evaluation utilities.
Meta-World
Source appears permissive; verify data terms · Benchmark suite of simulated manipulation tasks.
A simulated manipulation benchmark for multi-task and meta-reinforcement learning.
RLBench
Commercial use unclear · Large simulated task suite; source materials define current task count.
A simulated robot learning benchmark with many manipulation tasks in CoppeliaSim.
CALVIN
Commercial use unclear · Long-horizon simulated benchmark and demonstrations.
A benchmark for language-conditioned long-horizon robot manipulation in simulated environments.
ManiSkill
Source appears permissive; verify data terms · Simulation suite with tasks and environments maintained by the ManiSkill project.
A simulation benchmark and toolkit for manipulation skills and embodied AI policy evaluation.
Habitat datasets
Commercial use unclear · Multiple scene and task datasets under the AI Habitat ecosystem.
A family of embodied AI datasets and simulation assets for navigation and rearrangement research.
AI2-THOR
Source appears permissive; verify data terms · Interactive household simulation scenes and tasks.
An interactive simulated environment for embodied AI agents in household-like scenes.
BEHAVIOR
Commercial use unclear · Household activity benchmark and simulation assets.
A benchmark for household activities and embodied AI tasks in simulation.
ObjectFolder
Commercial use unclear · Object-centric multimodal assets; source materials define current object count and modalities.
A dataset family for object-centric physical properties, geometry, and multimodal perception research.
DexMV
Commercial use unclear · Dexterous manipulation demonstrations and visual observations; verify source for release details.
A dexterous manipulation dataset focused on multi-view visual observations and hand-object interaction.
RoboSuite
Source appears permissive; verify data terms · Simulation tasks and assets for manipulation research.
A simulation framework and benchmark suite for robot manipulation tasks.
RoboCasa
Commercial use unclear · RoboCasa365 source materials describe 365 everyday tasks, 2,500 kitchen environments, 600+ hours of human demonstration data, and 1,600+ hours of synthetic demonstrations.
A large-scale kitchen simulation framework and dataset family for everyday manipulation tasks in diverse household environments.
LIBERO
Commercial use unclear · Benchmark datasets are organized around multiple LIBERO task suites, including spatial, object, goal, and long-horizon manipulation variants.
A benchmark suite for lifelong robot learning and language-conditioned manipulation tasks.
RoboTurk
Commercial use unclear · Project materials describe over 100 hours of real robot data and thousands of successful manipulation demonstrations collected through remote users.
A large-scale teleoperation data collection platform and dataset family for robot manipulation tasks.
LeRobot datasets
Commercial use unclear · LeRobot documentation describes a standardized dataset ecosystem on Hugging Face Hub using Parquet for tabular data and MP4 for video observations.
A Hugging Face robotics dataset ecosystem and standardized dataset format for multimodal robot learning data.
FACET REVIEW PATHS
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.
INTERNAL LINKS
Continue the buyer workflow
Hugging Face robotics index
Scan the broader robotics dataset surface before narrowing into promoted profiles, comparisons, and custom collection specs.
Dataset changelog
Track source updates, licensing notes, and buyer-readiness changes that should trigger a renewed review.
Dataset fit checker
Score whether a public source is enough for the model, rights path, modalities, and target environment.
License risk checker
Separate source license language from contributor consent, redistribution, private-space risk, and model-use assumptions.
Data spec generator
Turn a public-source gap into a scoped capture request with sample QA, metadata, and delivery requirements.
Vendor alternatives hub
Compare data providers when the answer is not another public dataset but a better sourcing or capture route.
Data annotation companies
Use the company index to separate annotation vendors, data engines, marketplaces, and specialist capture teams.
EXTERNAL REFERENCES
Source context to verify
Scale AI physical AI data engine
Market context for why physical AI systems need custom, enriched, real-world data beyond generic labeling workflows.
LeRobot documentation
Robotics dataset and tooling context for Hugging Face based collection, sharing, conversion, and training workflows.
Open X-Embodiment
A cross-embodiment robotics dataset reference for comparing trajectory scale, robot diversity, and VLA training assumptions.
DROID dataset
A large in-the-wild robot manipulation dataset reference for real-world trajectory capture and deployment transfer risk.
TRUELABEL ROUTING
Need simulation data with cleaner rights?
Commission target-scoped data with contributor consent, capture metadata, sample QA, and delivery into your own storage.