Papers
1
Total Citations
16
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About
Yunjin Gu is a robotics researcher whose work centers on the dynamic modeling and control of industrial manipulators. His most impactful contribution lies in developing methods to accurately identify the dynamic parameters of robots—a critical factor for achieving high-performance control. In his highly cited 2010 study, Gu introduced a recursively-optimized trajectory approach using Fourier series parameterization to generate excitation trajectories for the AT2 robot. This work directly addressed the challenge of extracting accurate inertial and friction parameters, which are essential for model-based control schemes. With 16 citations, this paper has become a foundational reference for researchers working on robot identification and calibration. Gu’s contributions are particularly valuable for advancing the precision and reliability of industrial robots in manufacturing and automation, demonstrating how careful trajectory design can unlock better control performance and system understanding.
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