Yufeng Yao
Papers
1
Total Citations
2
H-Index
1
About
Yufeng Yao is a researcher whose work sits at the intersection of robotics, human-robot interaction, and assistive technology, with a particular focus on developing practical solutions for aging and mobility-impaired populations. His research has concentrated on Wheelchair Mounted Robotic Arms (WMRA), addressing critical challenges in real-time performance and intuitive interaction between users and robotic systems. A notable contribution is his work on laser-point detection using an improved target matching method, which enables more natural and accessible control interfaces for individuals with limited mobility in home environments. This research reflects a broader commitment to making assistive robotics both functionally robust and user-friendly in real-world settings. By leveraging computer vision techniques to interpret laser pointer inputs, Yao's approach offers a promising pathway toward greater autonomy for elderly and disabled users. While his citation record is still developing — with his 2018 work accumulating 2 citations — his research addresses a pressing societal need as global populations age rapidly. Students and researchers interested in assistive robotics, elderly care technology, or human-robot interaction will find Yao's work a relevant and practical reference point in this growing field.
Research Focus
Key Achievements
Top Papers
- 1