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NATURE · 2025 ·Vol. 647 ·期 8091 ·889-896 · IF 48.5

Slipknot-gauged mechanical transmission and robotic operation

Xue Yaoting,Cao Jiasheng,Feng Tao,Zhang Kaihang,Li Siyang,Hu Jiahao,Guo Haotian,Zhang Jinming,Song Yaoxian,Wang Zhuofan,Wang Lei,Huang Qishan,Zhou Haofei,Zhou Fanghao,Shen Jiliang,Fan Yaowei,Wang Zhe,Li Xinge,Wong Jie-Wei,Chen Zhiwei,Ruan Dongrui,Miao Zhikun,Zhang Bin,Zhou Enjie,Gan Letian,Wang Xuanqi,Cao Ertai,Chen Tong,Zou Weifeng,Zhang Junhui,Lu Haojian,Zhang Qinghai,Liu Song,Dong Huixu,Xiong Shiying,Peng Shuyou,Wong Tuck-Whye,Chen Yuanjie,Li Tiefeng,Chen Mingyu,Yang Xuxu,Yang Wei,Cai Xiujun

Mechanical transmission is essential in force-related activities ranging from the daily tying of shoe laces 1 to sophisticated surgical 2 and robotic operations 3 , 4 . Modern machines and robots typically use complex electronic devices designed to sense and limit force 5 , some of which still face challenges when operating space is limited (for example, in minimally invasive surgeries) 6 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.

CAS / MDL: 63148-62-9
研究领域: 机械工程 · 机器人学 · 生物医学工程 · 手术技术 · 智能材料与结构
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