Yiwei Huang
Papers
2
Total Citations
78
H-Index
2
About
Yiwei Huang is a robotics researcher whose work bridges assistive technology and autonomous navigation, with a focus on improving mobility for people who are blind and visually impaired (BVI). Their most impactful contribution is the development of a deep trail-following robotic guide dog, detailed in a 2018 paper with 73 citations. This work demonstrates how deep learning, trained in both virtual and real-world environments, can enable a robot to navigate pedestrian spaces by following trails, walls, and curbs—mimicking the guidance of a live animal. The research directly addresses a critical barrier to independent daily living for BVI individuals, offering a scalable alternative to traditional white canes or guide dogs. Huang also contributed to Team NCTU’s efforts in the RobotX Challenge, advancing AI-driven control for autonomous surface vehicles. While that paper has fewer citations, it reflects a broader interest in applying learning-based systems to real-world navigation, from land to water. Huang’s work stands out for its human-centered focus, combining rigorous technical development with a clear societal impact, and has helped shape the emerging field of robotic assistance for vulnerable populations.
Research Focus
Key Achievements
Top Papers
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- 2