Slipknot-gauged mechanical transmission and robotic operation

作者：Yaoting Xue, Jiasheng Cao, Tao Feng, Kaihang Zhang, Siyang Li, Jiahao Hu, Haotian Guo, Jinming Zhang, Yaoxian Song, Zhuofan Wang, L.Y Wang, Qi-Shan Huang, Haofei Zhou, Fanghao Zhou, Jiliang Shen, Yaowei Fan, Zhe Wang, Xinge Li, Jie‐Wei Wong, Zhiwei Chen, Dongrui Ruan, Zhikun Miao, Bin Zhang, Enjie Zhou, Letian Gan, Xuanqi Wang, Ertai Cao, Tong Chen, Weifeng Zou, Junhui Zhang, Haojian Lu, Qinghai Zhang, Song Liu, Huixu Dong, Shiying Xiong, Shuyou Peng, Tuck‐Whye Wong, Yuanjie Chen, Tiefeng Li, Mingyu Chen, Xuxu Yang, Wei Yang, Xiujun Cai · 发表于：Nature · 年份：2025 · DOI：10.1038/s41586-025-09673-w · 被引用次数：8 · 研究领域：Soft Robotics and Applications、Prosthetics and Rehabilitation Robotics、Surgical Simulation and Training

or when resources are scarce (for example, operations in remote areas without electricity). Here we describe an alternative slipknot-based mechanical transmission mechanism to control the intelligent operation of both human and robotic systems. Through topological design, slipknot tying and release can encode and deliver force with a consistency of 95.4% in repeating operations, which circumvents the need for additional sensors and controllers. When applied to surgical repair, this mechanism helped inexperienced surgeons to improve their knotting-force precision by 121%, enabling them to perform surgical knots as good as those of experienced surgeons. Moreover, blood supply and tissue healing after surgery were improved. The mechano-intelligence exhibited in slipknots may inspire investigations of knotted structures across multiple length scales. This slipknot-gauged mechanical transmission strategy can be widely deployed, opening up opportunities for resource-limited healthcare, science education and field exploration.