Scaling expert demonstrations alone does not enable generalist robot policies to improve from deployment. Real-world rollouts contain successes, suboptimal behavior, and failures: imitating every recorded action can reinforce poor behavior, while filtering out failures discards evidence of physical interactions and the...
Wen-Xuan Guo, Ying-Ping Liang, Zhao-Guo Wang et al.· 0 citations
To the knowledge, this work provides the first demonstration of real-time cross-terrain whole-body teleoperation on a humanoid robot, alongside object interaction, stable responses to missing supports, and robust recovery from falls.
Zi-Yang Cheng, Tian-Shu Tang, Jin-Xi Lan et al.· 0 citations
GigaWorld-Policy-0.5 preserves the training benefits of future visual dynamics while improving inference efficiency for robot control, and introduces a Mixture-of-Transformers architecture that separates visual dynamics modeling and action generation into specialized experts.
GigaWorld Team, Angen Ye, Ang-Yuan Ma et al.· arXiv.org· 3 citations
GigaBrain-WBC-0.5, the first Behavior World Model for humanoid whole-body control, is presented, which trains a causal Transformer to jointly predict its next action, next state, and the distribution over its next latent behavior command, so the network that acts also models how the environment shapes what it can do ne...
Zi-Yang Cheng, Tian-Shu Tang, Jin-Xi Lan et al.· 1 citation
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