Max Robotics — Global Service Robot Directory + US Certification

About

Renfeng Xue is a leading researcher in surgical robotics, with a primary focus on advancing laparoscopic surgical systems through innovative sensing and control technologies. Their work centers on addressing the critical challenge of force feedback in minimally invasive surgery, particularly the estimation and control of gripping forces in cable-pulley-driven surgical robots. Xue's major contributions include developing a position compensation control method based on cable-pulley system modeling (2017, 55 citations) and designing a novel Fiber Bragg Grating (FBG)-based tension sensor for the harsh sterilization environments of surgical end-effectors (2018, 46 citations). They have also pioneered sensorless grip force estimation techniques using neural networks optimized by genetic algorithms (2018, 5 citations), offering a practical solution for haptic feedback without additional sensors. Additionally, Xue has contributed to the design of hand-held mechatronic laparoscopic robots that provide intuitive master-slave motion mapping (2018, 3 citations). With over 135 total citations, Xue's research is instrumental in making robotic surgery safer and more precise, directly impacting the development of next-generation surgical tools.