Records
4
HF AUTHOR CLUSTER
haosulab robotics datasets
4 robotics-tagged HF records from haosulab, totaling 6,235 cumulative downloads. Some records cite published arxiv research.
DIRECT ANSWER
Author clusters consolidate every record from one publisher into a single buyer-review surface. haosulab ships 4 robotics datasets on Hugging Face. Top license: apache-2.0. Of those, 1 get a full standalone page, 1 get a shorter profile, and 2 are folded into this cluster.
Cumulative downloads
6,235
Top license
apache-2.0
DATASETS
All 4 robotics records from haosulab
4 of 4 datasets
ManiSkill_Demonstrations
Published Jul 2025 · apache-2.0 · haosulab
ManiSkill Demonstrations This dataset repo contains all of the latest ManiSkill demonstration datasets as well as some pretained model weights used to generate some demonstrations.
- 2,644 downloads
- 7 likes
- 1M<n<10M
ManiSkill_bridge_v2_real2sim
Published Sep 2024 · mit · haosulab
Assets for Real2Sim evaluation of the Bridge v2 dataset from https://github.com/simpler-env/SimplerEnv/
- 1,868 downloads
- 2 likes
- not specified
ManiSkill2
Published Mar 2025 · apache-2.0 · haosulab
ManiSkill2 Data Update: ManiSkill 3 has been released https://github.com/haosulab/ManiSkill/. It uses different datasets than ManiSkill2 so the data here is not expected to transfer over ManiSkill2 is a unified benchmark for learning…
- 894 downloads
- 11 likes
- 1M<n<10M
- Paper available
AI2THOR
Published May 2024 · cc-by-4.0 · haosulab
AI2THOR Scene/Object Dataset for ManiSkill This is a modified version of the Habitat Synthetic Scenes Dataset (HSSD) which is also modified based on the original AI2THOR scenes and assets in order to make it usable by ManiSkill.
- 829 downloads
- 1M<n<10M
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 haosulab 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.