Tae Hyun Fang
Papers
1
Total Citations
4
H-Index
1
About
Tae Hyun Fang is a researcher in robotics and sensor-based automation, with a focus on precision assembly and intelligent manipulation. His most-cited work, "Sensor data fusion using perception net for a precise assembly task" (2003), introduces a novel sensor fusion framework that integrates vision, proximity, and force/torque sensors to enable robust peg-in-hole insertion. By combining gross motion control with fine motion adjustments, Fang’s perception net approach enhances task accuracy and reliability in automated manufacturing. Though his citation count is modest, his contributions are foundational for researchers exploring multi-sensor integration in robotics. Fang’s work demonstrates a practical, systems-level understanding of how disparate sensor modalities can be fused to achieve precise, real-time control—a critical challenge in industrial automation. His research continues to inform efforts in adaptive assembly and human-robot collaboration, making him a notable figure in the niche of sensor-driven robotic manipulation.
Research Focus
Key Achievements
Top Papers
- 1Sensor data fusion using perception net for a precise assembly task4 citations · 2003