Qing Guo

Air Force Engineering University, Beijing University of Chemical Technology

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About

Qing Guo is a robotics and autonomous systems researcher whose work spans two compelling frontiers: bio-inspired aerial robotics and intelligent mobile robot navigation. His early research tackled the intricate challenge of controlling flapping-wing micro air vehicles (FMAVs), drawing inspiration from insect flight mechanics to develop fuzzy neural network (FNN)-based controllers capable of enabling stable hovering in biomimetic flying robots — a technically demanding problem that sits at the intersection of biology, control theory, and aerospace engineering. This 2008 contribution demonstrated the viability of soft computing approaches for managing the complex, nonlinear dynamics inherent to insect-like flight. More recently, Guo turned his attention to robust simultaneous localization and mapping (SLAM) for mobile robots, addressing one of the field's persistent practical challenges: the degradation of mapping performance caused by dynamic objects such as pedestrians. His improved ViBe (IVibe) algorithm introduced an adaptive background frame updating strategy to more reliably detect and handle moving objects in RGB-D environments. Together, these contributions reflect a consistent commitment to making autonomous robotic systems more reliable and capable in real-world conditions, earning recognition within the robotics research community.