Jiannan Wang
Papers
1
Total Citations
76
H-Index
1
About
Jiannan Wang is a leading researcher in surgical robotics and intelligent control systems, with a focus on enabling precise automation in complex, non-linear environments. His most-cited work, “Learning accurate kinematic control of cable-driven surgical robots using data cleaning and Gaussian Process Regression” (2014, 76 citations), addresses a critical challenge in medical robotics: achieving accurate control despite imprecise internal models caused by cable elasticity, tension variation, and backlash. By integrating data cleaning techniques with Gaussian Process Regression, Wang developed a learning-based approach that significantly improves the kinematic accuracy of cable-driven robots—systems essential for minimally invasive surgery. This work has been foundational for researchers and engineers working on adaptive control in soft and flexible robotic systems. Wang’s contributions bridge the gap between theoretical machine learning and practical robotic control, offering robust solutions for real-world surgical applications. His research continues to influence the development of safer, more reliable autonomous systems in healthcare, making him a key figure in the advancement of intelligent surgical assistance.
Research Focus
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Top Papers
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