Papers
2
Total Citations
20
H-Index
2
About
Tan Min is a pioneering researcher in intelligent robotics and automation, with a primary focus on robotic control systems and biomimetic underwater robotics. His seminal work on hybrid visual servoing control for robotic arc welding, published in 2005, introduced a novel structured light vision-based approach that integrates a Cartesian position control inner-loop with two outer visual control loops. This method significantly enhances precision and adaptability in industrial welding robots, laying the groundwork for advanced manufacturing automation. With 18 citations, this paper remains a key reference in visual servoing research. Tan Min also explored bio-inspired robotics, developing a back-propagation neural network predictive control system for three-link robotic fish. This work addresses the challenge of modeling complex hydrodynamic behaviors by using Central Pattern Generator data to predict swimming patterns, offering a practical solution for autonomous underwater vehicle control. While this 2008 paper has garnered 2 citations, it demonstrates his innovative cross-disciplinary approach. Tan Min’s contributions bridge industrial robotics and biomimetic systems, showcasing his ability to tackle real-world engineering challenges through intelligent control strategies.
Research Focus
Key Achievements
Top Papers
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- 2