Yufan Liao
Papers
1
Total Citations
70
H-Index
1
About
Yufan Liao is a researcher whose work sits at the intersection of robotics, sensor fusion, and intelligent manufacturing. Their most prominent contribution is the development of accurate, real-time 3-D tracking systems for following robots, achieved by fusing vision and ultrasonar information—a breakthrough that enhances human-robot interaction and industrial automation. This foundational paper has garnered 70 citations, underscoring its influence in advancing robotic perception and autonomous navigation. By solving the challenge of acquiring precise three-dimensional positions of moving targets, Liao’s research directly supports smarter, more responsive robotic systems in dynamic environments. Their work is particularly notable for bridging theoretical sensor fusion with practical, real-time applications, making it highly relevant for students and engineers working on collaborative robots, smart factories, and assistive technologies. Liao’s contributions continue to shape how robots perceive and interact with the world, laying critical groundwork for the next generation of intelligent, human-aware machines.
Research Focus
Key Achievements
Top Papers
- 1