Seon-Je Yang

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About

Seon-Je Yang is a robotics researcher whose work focuses on solving fundamental challenges in autonomous navigation and human-robot interaction. Yang’s primary research areas include geomagnetic localization for mobile robots, dynamic visual servoing for manipulators, and robust person-following algorithms. In a notable 2017 contribution, Yang proposed a novel method for indoor mobile robot localization using the Earth’s magnetic field. By exploiting how reinforced concrete, H-beams, and power systems distort geomagnetic signals, the technique transforms these environmental anomalies into distinctive regional features for position estimation—an approach that has garnered 5 citations. Yang also advanced precision control with a 2018 study on dynamic visual servoing for robot manipulators, introducing a dual-loop structure with a vision controller and a dynamic controller operating at different sampling speeds to achieve precise tracking. Additionally, Yang addressed a critical weakness in person-following robots by developing a classification-lock tracking approach that overcomes the limitations of single-shot initialization, improving robustness in complex, real-world environments. Through these contributions, Yang has demonstrated a consistent commitment to making robots more autonomous, perceptive, and reliable in unstructured settings.