Jong Il Yoon

Papers

Total Citations

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About

Jong Il Yoon is a researcher specializing in robotics, intelligent control systems, and human-robot interaction. His work focuses on developing advanced modeling and control techniques for robotic manipulators, particularly those using pneumatic artificial muscles (PAM), which offer compliant and safe actuation. In his most-cited paper, Yoon introduced a novel Forward Double NARX fuzzy model combined with a genetic algorithm to simultaneously identify both joints of a 2-axes PAM robot arm, effectively capturing the highly nonlinear coupling between links—a critical contribution to the field of soft robotics and bio-inspired actuation. This work has garnered 5 citations, reflecting its niche but foundational impact. Yoon also contributed to real-time face tracking for humanoid robots, proposing a system that uses skin color models and deformable ellipse matching on embedded platforms to enable autonomous person recognition and observation. With a total of 9 citations across his top papers, Yoon’s research bridges theoretical modeling and practical implementation, offering valuable insights for students and engineers working on intelligent robotic systems, nonlinear system identification, and human-robot interaction.