Cross-Embodiment Robot Foundation World Models with Latent Actions
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LAC-WM, a unified latent action space model, outperforms explicit action models in dexterous manipulation and LIBERO benchmark. Performance scales with pretraining embodiments. arXiv:2610.10846v1,
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- arXiv Robotics — research abstractsCross-Embodiment Robot Foundation World Models with Latent Actions
This research proposes LAC-WM, a robot world model that operates in a unified latent action space shared across diverse robot embodiments. It outperforms explicit action-conditioned models in dexter, manipulation tasks and the LIBERO benchmark, demonstrating the benefits of a unified action space for cross-embodiment learning.
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