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About

Dr. Qingmin Liao is a robotics researcher whose work focuses on multi-robot coordination, humanoid robot control, and soft robotics sensing. His early career contributions established foundational algorithms for multi-robot cooperation in human-robot mixed environments, including an intelligent algorithm combining statistical methods with artificial neural networks for obstacle-rich settings (2007, 5 citations). He also advanced robot manipulator control through motion track predictive control with flexible curve calculation (2007, 3 citations) and developed improved task-oriented force feedback control methods for humanoid robots operating alongside humans (2007, 2 citations). His work on double video signal-based location and stereo video generation systems (2007, 2 citations) addressed critical perception challenges for humanoid platforms. More recently, Dr. Liao has contributed to the emerging field of soft robotics, designing a soft joint shape measurement device using Fiber Bragg Grating sensors with a simple demodulating system (2022, 4 citations)—addressing the difficult problem of continuous shape estimation for complex joints. He also proposed MR-GMMExplore, a multi-robot exploration system using Gaussian Mixture Models for communication-limited unknown environments (2022, 3 citations). With a career spanning foundational multi-robot algorithms to cutting-edge soft sensing, Dr. Liao’s research demonstrates sustained impact across multiple generations of robotic systems.