Yehui Li
Papers
17
Total Citations
155
H-Index
7
About
Yehui Li is a pioneering researcher at the intersection of medical robotics, autonomous control, and minimally invasive surgical systems. Their work spans robotic endoscopy, soft robotics, visual servo control, and neural network-based motion planning, with a particular focus on reducing the clinical burden of gastrointestinal and neurosurgical procedures. Li's most impactful contribution, garnering 38 citations, introduced a predefined-time convergent adaptive neural network for 4-DOF visual servoing of flexible robotic endoscopes — addressing the longstanding challenge of autonomous endoscope manipulation under real-world noise and misorientation conditions. Complementing this, their series of electromagnetically actuated soft-tethered colonoscope systems, collectively accumulating over 35 citations, demonstrates a sustained effort to make colonoscopy safer and more patient-friendly through semi-autonomous and hybrid vision-magnetic control frameworks. Equally notable is Li's biomimetic robotics work, including a gastropod-inspired soft snail robot and a wet-adhesive crawling robot, reflecting a creative approach to locomotion in challenging biological environments. More recently, their simultaneous polyp and lumen detection framework and flexible magnetoelastic strain sensors signal a broadening into AI-driven surgical perception and wearable sensing. Across disciplines, Li's research consistently advances the autonomy, safety, and clinical applicability of next-generation surgical robotic systems.
Research Focus
Key Achievements
Top Papers
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