ModelFeatured
DreamerV3
General world-model RL agent mastering diverse domains including robot-like continuous control.
ModelFeaturedFully open
TD-MPC2
Model-based RL with latent dynamics — strong continuous-control and robot-oriented results.
Why: Strong open model-based RL for continuous control
Overview
TD-MPC2 is catalogued on Embodied AI Hub as a curated model for embodied AI builders.
Model-based RL with latent dynamics — strong continuous-control and robot-oriented results.
Why it matters: Strong open model-based RL for continuous control
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
- Model-based RL with latent dynamics — strong continuous-control and robot-oriented results.
- Type: model; categories: model
- 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