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title

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GenH2R: Learning Generalizable Human-to-Robot Handover via Scalable Simulation, Demonstration, and Imitation

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author

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2026-02-27 17:42:11

raw text

GenH2R: Learning Generalizable Human-to-Robot Handover via Scalable Simulation, Demonstration, and Imitation GenH2R: Learning Generalizable Human-to-Robot Handover via Scalable Simulation, Demonstration, and Imitation Zifan Wang* 1,3 , Junyu Chen* 1,3 , Ziqing Chen 1 , Pengwei Xie 1 , Rui Chen 1 , Li Yi† 1,2,3 , 1 Tsinghua University, 2 Shanghai Artificial Intelligence Laboratory, 3 Shanghai Qi Zhi Institute Paper arXiv Video Code Abstract This paper presents GenH2R , a framework for learning generalizable vision-based human-to-robot (H2R) handover skills. The goal is to equip robots with the ability to reliably receive objects with unseen geometry handed over by humans in various complex trajectories. We acquire such generalizability by learning H2R handover at scale with a comprehensive solution including procedural simulation assets creation...

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