Guoshu Xu
Papers
1
Total Citations
6
H-Index
1
About
Guoshu Xu is a researcher whose work lies at the intersection of industrial robotics, computer vision, and automation systems. His primary research focuses on developing precise calibration methods for robotic systems, particularly eye-in-hand configurations where cameras are mounted directly on robot arms. In his most-cited work, "A Scene Feature Based Eye-in-Hand Calibration Method for Industrial Robot" (2020), Xu introduced a novel approach that leverages scene features to improve calibration accuracy without requiring specialized calibration targets. This contribution addresses a critical challenge in industrial automation—ensuring that robots can accurately perceive and interact with their environments. While his citation count is still growing, with this paper garnering 6 citations, the work demonstrates foundational potential for practical applications in manufacturing and assembly lines. Xu's research is particularly valuable for students and engineers seeking robust, cost-effective solutions for robot vision systems. His focus on real-world industrial constraints, such as ease of deployment and adaptability to dynamic environments, marks him as a practitioner-oriented researcher whose work bridges theoretical calibration algorithms with tangible automation needs.
Research Focus
Key Achievements
Top Papers
- 1