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Mechanical transmission is essential in force-related activities ranging from the daily tying of shoe laces1 to sophisticated surgical2 and robotic operations3,4. Modern machines and robots typically use complex electronic devices designed to sense and limit force5, 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.
Pubmed ID: 41299050
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Computer vision and machine learning software library which provides a common infrastructure for computer vision applications. The algorithms within the library can be used to detect and recognize faces, identify objects, classify human actions in videos, track camera movements and moving objects, extract 3D models of objects, produce 3D point clouds from stereo cameras, stitch images together to produce a high resolution image of an entire scene, find similar images from an image database, and follow eye movements, recognize scenery and establish markers to overlay it with augmented reality. It has C++, C, Python, Java and MATLAB interfaces.
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