Papers
2
Total Citations
29
H-Index
2
About
Qidong Li is a researcher focused on advancing the precision and safety of industrial robotics. His primary contributions lie in robot calibration and dynamic obstacle detection, addressing critical challenges in manufacturing automation. Li’s most influential work, “A New Fixed Axis-Invariant Based Calibration Approach to Improve Absolute Positioning Accuracy of Manipulators” (2020), has garnered 26 citations. In this study, he introduced a novel calibration method that determines Denavit-Hartenberg (DH) frames and parameters by measuring first and modeling after, effectively streamlining the traditionally cumbersome modeling process and enhancing absolute positioning accuracy in industrial manipulators. This approach offers a practical solution for improving robot performance without complex system overhauls. Additionally, Li has explored dynamic obstacle detection in robot workspaces, as seen in his 2017 paper (3 citations), which proposes a background compensation technique to quickly identify moving obstacles along predefined routes, bolstering operational safety. Through these works, Li demonstrates a commitment to both precision engineering and real-time safety in robotics, making his research valuable for students and engineers seeking to optimize industrial automation systems.
Research Focus
Key Achievements
Top Papers
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