Xing Gu
Papers
2
Total Citations
20
H-Index
2
About
Xing Gu is a researcher specializing in multi-robot coordination, industrial automation, and mechatronic systems for manufacturing processes. Their major contributions lie in developing calibration and collaborative control methods for industrial robots, particularly in grinding and deburring applications. Gu’s most cited work, "Base frame calibration for multi-robot cooperative grinding station by binocular vision" (2017, 17 citations), addresses the challenge of repetitive calibration in high-density robot environments by proposing a novel non-contact method using binocular vision, significantly improving precision and efficiency. In another notable study, "A mechatronic approach for double robots collaborative deburring of die casting" (2017, 3 citations), Gu presents an integrated approach where dual robots deburr die castings on both sides simultaneously, with a mathematical model of cutting force to enhance quality and throughput. This work highlights Gu’s focus on practical, industry-driven solutions that bridge robotics, vision systems, and process optimization. With a growing citation footprint, Xing Gu’s research is valuable for engineers and researchers advancing collaborative robotics in manufacturing, offering scalable methods for calibration and multi-robot coordination that reduce downtime and improve product consistency.
Research Focus
Key Achievements
Top Papers
- 1
- 2