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Whole-Body Humanoid Control via Stochastic Motion Tokenization

arXiv cs.RO

This study proposes using a stochastic motion tokenizer to generate concise discrete motion representations that can be fed directly into a whole-body tracking policy to execute dance, fighting, and walking motions on the Unitree G1. At matched capacity, the tokenizer reconstructs Unitree G1 motions better than FSQ and VQ-VAE. In real-robot demonstrations, each generated motion lasted 16.8 seconds, and a 35-second fighting-to-dance sequence was completed.

Part of the event: Random Motion Tokenization for Humanoid Whole-Body Control

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