Guiling Yang

University of Minnesota, Chinese Academy of Sciences

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About

Guiling Yang’s research lies at the intersection of robotics, dynamics, and sensor systems, with a focus on understanding and controlling flexible structures in robotic manipulators. Her foundational work on the dynamic modeling of a one-link robot manipulator, which simultaneously accounts for both structural and joint flexibility, has been cited 38 times and remains a key reference for researchers tackling the complexities of flexible robots. This contribution highlighted the critical importance of including joint flexibility in dynamic models—a nuance often overlooked but essential for accurate motion prediction and control. Earlier, Yang contributed to the development of the Minnesota Scanner, a pioneering sensor system for three-dimensional tracking of moving body segments. With 23 citations, this work demonstrated potential applications in human motion analysis and robot endpoint control. More recently, she has advanced the field by addressing parameter identification in flexible robotic joints using multi-sensor information, a challenging problem critical for real-world mechatronic systems. Yang’s career reflects a sustained commitment to bridging theoretical modeling with practical sensing solutions, making her work valuable to both robotics engineers and biomechanics researchers.