Ching-I Huang
Papers
6
Total Citations
130
H-Index
6
About
Ching-I Huang is a robotics and artificial intelligence researcher whose work sits at the dynamic intersection of autonomous navigation, human-robot interaction, and assistive technology. Huang's research addresses some of the most pressing challenges in modern robotics, from enabling independent mobility for blind and visually impaired individuals to coordinating heterogeneous robot teams in complex, real-world environments. Among Huang's most recognized contributions is a deep reinforcement learning-based assistive guiding robot that leverages UWB beacons and semantic feedback to help visually impaired users navigate pedestrian environments — a paper that has earned 46 citations and highlights a strong commitment to socially impactful robotics. Complementing this, Huang has pioneered cross-modal contrastive learning using millimeter-wave radar for robust navigation in adverse conditions (26 citations) and developed collaborative unmanned ground vehicle and blimp systems for search-and-rescue missions (20 citations). Huang also advances human-robot collaboration through innovative interfaces, including a VR-based teleoperation framework (20 citations) and federated learning approaches for robot grasping in healthcare handover scenarios. Together, these contributions — spanning over 130 cumulative citations — reflect a researcher who consistently bridges theoretical rigor with practical, human-centered applications that push the boundaries of autonomous and assistive robotics.
Research Focus
Key Achievements
Top Papers
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- 5Fed-HANet: Federated Visual Grasping Learning for Human Robot Handovers11 citations · 2023
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