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About

Hung-Hsiu Yu’s research lies at the intersection of mobile robotics, sensor fusion, and human–robot interaction, with a focus on enabling autonomous navigation and assistive technologies. His most cited work, “Visual Localization for Mobile Robots Based on Composite Map” (8 citations), introduces a two-stage method that fuses laser range finder and camera data to construct a composite map for robust visual localization—a foundational contribution to autonomous robot positioning. Yu also advanced adaptive tracking control for nonholonomic mobile robots (4 citations), experimentally verifying controllers that handle complex, unstructured environments. In “Concurrent Multiple Cameras Calibration and Robot Localization from Visual and 3D Inertial Measurements” (3 citations), he developed an inertial sensor module fusing accelerometer, gyroscope, and vision data for accurate 3D pose estimation, enhancing navigation reliability. Notably, Yu’s work on a lower-limb mobile training robot (3 citations) demonstrates his commitment to rehabilitation robotics, designing motion control systems for passive and resistive joint exercises. He also explored companion robots with facial expressions and face recognition (2 citations), integrating 12 degrees of freedom for expressive interaction. With a career spanning sensor fusion, multi-robot navigation, and assistive robotics, Yu’s contributions—though modest in citation counts—reflect a practical, interdisciplinary approach to solving real-world robotic challenges.