Dataset
X-VLA
[ICLR 2026] The offical Implementation of "Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model"
Dataset
M2DGR
M2DGR： a Multi-modal and Multi-scenario Dataset for Ground Robots(RA-L2021 & ICRA2022)
Overview
M2DGR is catalogued on Embodied AI Hub as a curated dataset for embodied AI builders.
M2DGR： a Multi-modal and Multi-scenario Dataset for Ground Robots(RA-L2021 & ICRA2022)
Why it matters: M2DGR： a Multi-modal and Multi-scenario Dataset for Ground Robots(RA-L2021 & ICRA2022)
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
- M2DGR： a Multi-modal and Multi-scenario Dataset for Ground Robots(RA-L2021 & ICRA2022)
- Type: dataset; categories: real-world
- Catalogued via weekly curator agent
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.
Caveats & pitfalls
- Hub cards are curated summaries — always verify upstream docs.
- Auto-ingested entries may need a later human polish pass.
Content reviewed 2026-08-10