ModelFeatured
RDT-1B
Diffusion foundation model for bimanual skill, trained with AgiBot and public data.
1.2BFully openData: AgiBot World + 公开数据Updated 2026-01-21
ModelFully open
BAKU
Efficient multi-task policy architecture for robot learning from demonstrations.
Why: Efficient multi-task IL policy design
Overview
BAKU is catalogued on Embodied AI Hub as a curated model for embodied AI builders.
Efficient multi-task policy architecture for robot learning from demonstrations.
Why it matters: Efficient multi-task IL policy design
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
- Efficient multi-task policy architecture for robot learning from demonstrations.
- Type: model; categories: model
- Catalogued for coverage completeness
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