Mengyao Fan
Papers
2
Total Citations
27
H-Index
2
About
Mengyao Fan is a rising figure in industrial robotics, specializing in kinematic calibration and precision engineering. Her research focuses on developing novel methods to enhance the positioning accuracy of industrial robots, a critical challenge in modern manufacturing. Fan’s most impactful work, “A novel calibration method for kinematic parameter errors of industrial robot based on Levenberg–Marquard and Beetle Antennae Search algorithm” (2023, 22 citations), introduces a hybrid optimization approach that combines the Levenberg–Marquardt algorithm with the bio-inspired Beetle Antennae Search. This method significantly improves error compensation by leveraging the Modified Denavit–Hartenberg model, offering a practical solution for high-precision tasks. Her subsequent study, “A robot kinematic parameter error calibration method based on the 3D artifact and trigger probe” (2025, 5 citations), further advances the field by integrating 3D artifacts and trigger probes for more robust calibration. Fan’s contributions are notable for their innovative fusion of classical and nature-inspired algorithms, addressing real-world industrial needs. Her work has garnered attention for its potential to reduce downtime and enhance robot reliability, marking her as a promising researcher in robotics and automation.
Research Focus
Key Achievements
Top Papers
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- 2