Model-based control can directly execute specified objectives, while learning can amortize such behaviors into reactive policies, making their combination a natural solution to multi-stage manipulation. We introduce Semantically UNified (SUN) Programs, typed executables that compile grounded relations into aligned opti...
Wei-Qi Wang, Zhi Li, Yuliang Lei et al.· 0 citations
Collecting robot hand-object interaction data is costly and embodiment-specific, yet abundant human-object videos remain unusable for robot training. We present RoboEdit, a human-to-robot video editing suite that transforms human manipulation videos into action-consistent, physically plausible robot videos with aligned...
Yaowei Guo, Zeng Tao, Yuxin Jiang et al.· 1 citation
The results establish that simulation-screened task semantics can effectively amortize control into robust policies, without demonstrations or manual dense rewards, unifying symbolic planning and data-driven execution.
Wei-Qi Wang, Zhi Li, Yuliang Lei et al.· 0 citations
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