Cheoljong Yang

Papers

Total Citations

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About

Cheoljong Yang is a researcher in human-robot interaction (HRI), specializing in gesture-based control systems that make robot operation more intuitive. His work centers on developing motion primitives and statistical models to interpret human hand gestures for seamless robot command. Yang’s major contributions include proposing a flexible gesture set design framework based on angular tendency analysis of sign languages and practical hand motions, enabling more natural HRI interfaces. He also advanced Hidden Markov Model (HMM)-based hand gesture recognizers for real-time robot control, where a humanoid robot processes webcam images to extract hand motion features. Though his most-cited papers—"Motion primitives for designing flexible gesture set in Human-Robot Interface" (4 citations) and "Robot User Control System using Hand Gesture Recognizer" (2 citations)—have modest citation counts, they represent foundational steps in gesture-driven robotics. Yang’s work is notable for bridging statistical analysis with practical interface design, offering a systematic approach to building customizable gesture vocabularies. His research remains relevant for students and engineers exploring non-verbal human-robot communication, emphasizing efficiency and adaptability in control systems.