Papers
1
Total Citations
2
H-Index
1
About
Yutao Zhao is a researcher specializing in precision robotics, computer vision, and automated measurement systems. His most notable contribution is the development of a non-contact, computer vision-based method for measuring positioning errors in robotic manipulator arms, introduced in his 2018 paper "Robotic manipulator arms positioning error measurement using image registration." This work presents a repeatability assessment scheme for XY-Theta platforms using phase correlation-based image registration, offering a significant advantage over traditional contact-based measurement techniques by eliminating mechanical interference and simplifying implementation. Although his highly cited paper has garnered 2 citations, the work's practical relevance lies in its potential to enhance calibration and accuracy in industrial robotics and automation. Zhao's research bridges the gap between image processing and robotic metrology, providing a cost-effective, easy-to-deploy solution for real-time error assessment. His contributions are particularly valuable for students and researchers exploring vision-guided robotics, precision manufacturing, and non-invasive diagnostic tools for robotic systems.
Research Focus
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Top Papers
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