Yufeng Xiao
Papers
1
Total Citations
2
H-Index
1
About
Yufeng Xiao is a researcher specializing in robotics, autonomous systems, and radiation detection, with a particular focus on developing intelligent methods for locating radioactive sources in complex environments. Their most notable contribution involves a novel autonomous source-finding methodology that combines particle filter algorithms with artificial potential field techniques, enabling mobile robots to search for and precisely locate radioactive sources with significantly improved accuracy. This work addresses a critical challenge in nuclear safety and hazardous environment robotics, where human intervention is dangerous or impractical. By equipping mobile robots with radiation detectors and integrating probabilistic filtering with potential field navigation, Xiao's approach offers a meaningful step forward in automating radiological surveys and emergency response scenarios. Published in 2020, this research has begun attracting attention within the robotics and nuclear safety communities, accumulating citations that reflect its relevance to an emerging interdisciplinary field. Xiao's work sits at the intersection of robotics, sensor fusion, and radiation safety, contributing practical solutions that have implications for nuclear facility monitoring, disaster response, and environmental radiation assessment — areas of growing global importance.
Research Focus
Key Achievements
Top Papers
- 1