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Contact Trajectory Prompting: In-Context Transfer of Contact-Rich Behaviors from a Single Demonstration

Xian Nie, Yujie Zang, Yuhang Zheng, Yupeng Zheng, Songen Gu, Wendi Chen, Chuan Wen, Cewu Lu, Wenchao Ding, Junchi Yan, Shuicheng Yan
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摘自论文摘要

In-context robot learning enables robots to acquire new behaviors from demonstrations without test-time parameter updates. However, visual and kinematic specifications alone may not distinguish contact-rich behaviors that share similar motions but require different interaction intensities or patterns.

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