SCSP is a cascaded optimization framework using a surrogate contact model and discrete-continuous search to enable simultaneous contact selection and planning for robust contact-rich manipulation.
arXiv preprint arXiv:2602.06035 , year=
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SUGAR turns diverse human videos into deployable humanoid loco-manipulation policies via automated prior extraction, physics refinement, and hierarchical distillation, showing scaling with data volume and zero-shot real-world transfer on six tasks.
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Simultaneous Contact Selection and Planning for Contact-Rich Manipulation with Cascaded Optimization
SCSP is a cascaded optimization framework using a surrogate contact model and discrete-continuous search to enable simultaneous contact selection and planning for robust contact-rich manipulation.
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SUGAR: A Scalable Human-Video-Driven Generalizable Humanoid Loco-Manipulation Learning Framework
SUGAR turns diverse human videos into deployable humanoid loco-manipulation policies via automated prior extraction, physics refinement, and hierarchical distillation, showing scaling with data volume and zero-shot real-world transfer on six tasks.