Cross-Embodiment Robot Foundation World Models with Latent Actions
The Latent Action-Conditioned Robot World Model (LAC-WM) was introduced to improve robot world models across different robot bodies. It uses a unified latent action space shared by diverse embodiments, which outperforms explicit action conditioning. This unified space allows performance to scale positively with the number of pretraining robots, unlike explicit methods which degrade.