Than-Long Nuyen

Laboratoire d'Informatique, du Traitement de l'Information et des Systèmes

Papers

Total Citations

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About

Than-Long Nuyen is a researcher whose work sits at the intersection of robotics, fuzzy logic, and computer vision, with a particular focus on enabling humanoid robots to perceive and interact with their environments more intelligently. His most cited paper, "Color Recognition for NAO Robot Using Sugeno Fuzzy System and Evidence" (2015, 5 citations), addresses a fundamental challenge in robotics: how to make a robot reliably recognize colored objects using only its onboard cameras. Rather than relying on rigid, threshold-based methods, Nuyen introduced a Sugeno-type fuzzy inference system to model the complex, nonlinear mapping between HSV color space values and linguistic color labels. This approach allows the NAO robot to handle the variability of real-world lighting and surface textures with greater robustness. By integrating fuzzy logic with evidential reasoning, his work provides a more human-like, uncertainty-aware method for visual perception—a critical step toward more autonomous and adaptable robots. Though his citation count is modest, the conceptual contribution is significant for researchers working on low-cost, vision-based robotic platforms. Nuyen’s research exemplifies how soft computing techniques can bridge the gap between raw sensor data and meaningful robotic action.