Yao‐Hui Huang

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About

Yao-Hui Huang is a researcher at the forefront of soft robotics and advanced control systems, with a particular focus on bridging the gap between theoretical control methods and real-world robotic applications. His key research areas include model predictive control (MPC), disturbance estimation, and the dynamic control of soft robotic manipulators. Huang's major contribution lies in the development of offset-free MPC strategies that enable precise, high-speed manipulation with soft, deformable structures—a notoriously challenging task due to their nonlinear and compliant nature. His notable work, "Offset-free Model Predictive Control: A Ball Catching Application with a Spherical Soft Robotic Arm" (2021), demonstrates a novel integration of linear models with online disturbance estimation to systematically compensate for model deviations, achieving fast and accurate control in dynamic tasks. This paper has garnered 5 citations, reflecting its emerging impact in the field. Huang's research is instrumental in advancing the practical deployment of soft robots for tasks requiring both safety and precision, such as human-robot interaction and agile manipulation. His work continues to inspire new approaches to robust, real-time control in soft robotics.