Young‐Cheol Lim

Papers

Total Citations

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About

Young-Cheol Lim is a researcher whose work lies at the intersection of autonomous robotics, intelligent sensing, and machine perception. His primary research areas include position sensing systems, material recognition, and vision-based localization for mobile robots. Lim’s major contributions include the design of a magnet-based position sensing system for autonomous vehicle robots, which leverages reliable magnetic sensing technology for precise position measurement and guidance—a foundational element for autonomous navigation. He also developed a novel approach for material temperature response recognition using curve fitting and fuzzy neural networks (FNN), enabling material identification even under varying ambient temperatures. In the realm of ubiquitous robotics, Lim proposed a practical method for correcting distorted images from fisheye lenses in vision-based self-localization systems using ceiling artificial landmarks, addressing critical challenges in real-time, wide-field-of-view applications. While his citation counts (ranging from 4 to 9) reflect focused, niche contributions, his work demonstrates a consistent commitment to solving practical, real-world problems in autonomous systems. Lim’s research is particularly notable for its integration of sensor fusion, real-time processing, and adaptive intelligence, making his findings valuable for engineers and researchers developing robust, cost-effective solutions for autonomous vehicle and mobile robot navigation.