Yongyu Chen
Papers
1
Total Citations
5
H-Index
1
About
Yongyu Chen is a robotics researcher whose work centers on advancing vision-guided manipulation systems, with a particular focus on hand-eye calibration—a critical prerequisite for any robot manipulator relying on visual feedback. His major contribution lies in developing a simple, generic, and real-time method for accurate hand-eye calibration using 3D vision sensors, a technology that has rapidly gained popularity in modern robotics. His 2019 paper, "A Simple and Generic Method for Real-time Accurate Hand-eye Calibration Using a 3D Vision Sensor," addresses a pressing gap in the field by proposing a unified approach that works for both eye-to-hand and eye-in-hand configurations. This work has garnered 5 citations, reflecting its practical significance and foundational role in enabling more precise and efficient robotic operations. By tackling the challenge of real-time calibration with 3D sensors, Chen’s research directly supports applications in industrial automation, autonomous assembly, and human-robot collaboration. His method stands out for its simplicity and adaptability, making it accessible for both academic researchers and industry practitioners seeking to deploy robust vision systems.
Research Focus
Key Achievements
Top Papers
- 1