DatasetFeatured
RoboTwin 2.0
RoboTwin 2.0: scalable dual-arm data generator and benchmark with domain randomization (50 tasks, 5 embodiments, RoboTwin-OD).
growingResearchBest for finetuneBest for evalBimanualUpdated 2026-09-22
DatasetFeatured
ARNOLD
Language-conditioned household manipulation benchmark and assets for embodied agents.
Why we recommend it
Household language-conditioned manipulation benchmark
Overview
ARNOLD is catalogued on Embodied AI Hub as a curated dataset for embodied AI builders.
Language-conditioned household manipulation benchmark and assets for embodied agents.
Why it matters: Household language-conditioned manipulation benchmark
Use the official repository and docs as the source of truth for install pins, licenses, and hardware requirements.
Who it is for
Researchers, students, and builders comparing open embodied stacks.
Key highlights
- Language-conditioned household manipulation benchmark and assets for embodied agents.
- Type: dataset; categories: dataset
- Marked recommended on the hub
When to use
- You are mapping the open embodied AI landscape
- You need a starting URL and judgment note before deep-diving
When not to use
- You need production SLAs or certified industrial support only
- License or hardware constraints are incompatible with your deployment
Getting started
- 1Open the official URL and read README install pins.
- 2Skim license and citation requirements.
- 3Run the smallest official example before scaling experiments.
- 4Cross-link related hub resources (sim / data / policy) for a full stack.
Papers & reading
Caveats & pitfalls
- Hub cards are curated summaries — always verify upstream docs.
- Stars and dates drift; treat extra.stars as approximate.
Content reviewed 2026-07-28
Comments
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