Guowei Zhong
Papers
2
Total Citations
11
H-Index
2
About
Guowei Zhong is a researcher specializing in robotic vision and hand-eye calibration, with a focus on enhancing the precision of robot manipulation systems. His major contributions lie in developing novel calibration methods that address the persistent challenge of random errors in vision-guided robotics. Zhong’s most cited work, a 2023 paper proposing a binocular vision-robot hand-eye calibration method using dual nonlinear optimization and sample screening, has garnered 7 citations, reflecting its relevance to improving operational accuracy. In a complementary study, he introduced a double-layer Levenberg–Marquardt optimization (DLMO) approach with outlier sample screening for monocular vision robots, achieving 4 citations by effectively reducing the influence of random errors. These methods represent significant advances in robust calibration, offering practical solutions for real-world robotic systems where precision is critical. Zhong’s research is particularly notable for its dual-layer optimization framework, which systematically filters outlier data points to enhance calibration reliability. His work has implications for industrial automation, surgical robotics, and autonomous systems, positioning him as a rising contributor to the field of robot vision and control.
Research Focus
Key Achievements
Top Papers
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- 2