arXiv AI By Shuoheng Zhang, Yifu Yuan, Hongyao Tang, Yan Zheng, Qiaojun Yu, Pengyi Li, Guowei Huang, Helong Huang, Xingyue Quan, Jianye Hao

ForceFlow: Learning to Feel and Act via Contact-Driven Flow Matching

Read the original on arXiv AI →

ForceFlow is a force-aware reactive framework that uses flow matching to improve contact-rich manipulation. It fuses force signals asymmetrically, treats force as a global regulator, and employs a joint prediction paradigm to couple force and motion. The approach splits tasks into a vision-dominant localization stage and a touch-dominant execution stage, using a Vision-to-Force handover to separate spatial generalization from contact regulation.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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