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 2026-08-10
DatasetFeatured
ManiSkill3 assets & demos
GPU-parallel ManiSkill3 task assets and demonstration sets for large-scale policy learning.
Why we recommend it
Native demo/assets layer for ManiSkill3 training
Overview
ManiSkill3 assets & demos is a curated dataset on Embodied AI Hub.
GPU-parallel ManiSkill3 task assets and demonstration sets for large-scale policy learning.
Why it matters: Native demo/assets layer for ManiSkill3 training
Always verify install pins, licenses, and hardware requirements on the official site before production use.
Who it is for
Builders mapping open embodied stacks; researchers comparing SOTA baselines.
Key highlights
- GPU-parallel ManiSkill3 task assets and demonstration sets for large-scale policy learning.
- Type: dataset; tags: 数据集, 仿真, GPU, 操作
- Hub recommended
When to use
- You need this category of open resource in your stack map
- You are shortlisting baselines before deep evaluation
When not to use
- License or hardware constraints block adoption
- You only need a closed commercial stack with vendor SLA
Getting started
- 1Open the official URL and read the README / model card.
- 2Check license and citation requirements.
- 3Run the smallest official example before scaling.
- 4Cross-link related hub resources for a full pipeline.
Caveats & pitfalls
- Hub cards are curated summaries — verify upstream docs.
- Stars and release names drift; treat metadata as approximate.
Content reviewed 2026-07-28