Yongjie Liu
Papers
1
Total Citations
4
H-Index
1
About
Dr. Yongjie Liu is a robotics researcher whose work centers on advancing industrial automation through precise sensor integration and calibration techniques. His primary research areas include hand-eye calibration for robotic systems, 3D vision-based perception, and the application of dual quaternion mathematics to improve robotic accuracy. Dr. Liu’s major contribution lies in developing a novel hand-eye calibration method for industrial robots equipped with 3D depth cameras, as presented in his most-cited 2022 paper. By designing a set of 3D cube-shaped calibrators and leveraging point-to-point correspondence registration, his approach simplifies the traditionally complex calibration process, enabling more reliable and efficient robot-camera coordination in manufacturing environments. This work has garnered attention from peers, accumulating 4 citations and establishing a foundation for further research in vision-guided robotics. Dr. Liu’s innovative use of dual quaternions for calibration represents a significant step toward more flexible and accurate automation systems, making his research particularly valuable for students and engineers working on robotic perception and industrial integration.
Research Focus
Key Achievements
Top Papers
- 1