Joon Kyu No

Papers

Total Citations

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About

Joon Kyu No’s research career bridges foundational work in robotic sensing with cutting-edge assistive robotics. His early contribution, “Adaptative Ultrasonic Range-Finder for Robotics” (1989), introduced adaptive signal processing for ultrasonic sensors, a key enabler for autonomous navigation in cluttered environments. Though its 4 citations reflect the era’s smaller research community, this work laid groundwork for later sensor fusion in mobile robotics. Three decades later, No addressed a critical challenge in wearable robotics with “Development of the Algorithm of Locomotion Modes Decision based on RBF-SVM for Hip Gait Assist Robot” (2020). This study pioneered a machine learning approach—Radial Basis Function Support Vector Machine (RBF-SVM)—to automatically detect locomotion modes (level walking, stair ascent, and stair descent) for hip exoskeletons. By enabling real-time, accurate mode switching, the algorithm overcomes a key limitation of universal hip assist robots, which previously struggled with adaptive support across terrains. Though citation counts remain modest, No’s trajectory from sensor adaptation to intelligent gait control demonstrates a sustained commitment to practical robotics, with his 2020 work offering a direct pathway to safer, more responsive assistive devices for mobility-impaired users.