Xinggang Liu
Papers
2
Total Citations
12
H-Index
2
About
Xinggang Liu is a pioneering researcher in the field of robotic calibration and precision manufacturing. His work focuses on developing innovative methods to enhance the accuracy and autonomy of industrial robots, particularly in arc-welding and polishing applications. Liu’s major contributions include the introduction of autonomous calibration techniques that allow robots to self-correct positioning errors using simple probes and constraint planes, eliminating the need for precisely known external references. His 2006 paper on autonomous calibration for polishing robots has garnered 7 citations, while his 2005 work on neural network-based calibration for arc-welding robots has received 5 citations. Notably, Liu’s neural network approach stands out for its ability to calibrate a robot using only its nominal model, significantly reducing the complexity and cost of traditional calibration processes. These achievements have laid a foundation for more flexible and cost-effective robotic systems, making his research highly relevant for students and engineers working on robot accuracy, adaptive control, and intelligent manufacturing.
Research Focus
Key Achievements
Top Papers
- 1Autonomous Calibration Research of Polishing Robot7 citations · 2006
- 2Calibration of the arc-welding robot by neural network5 citations · 2005