Guoying Zhang

Guangdong University of Technology, China University of Mining and Technology

Papers

Total Citations

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About

Guoying Zhang is a robotics researcher whose work sits at the intersection of safe human-robot interaction and 3D scene understanding. Her key contributions span two critical areas: real-time motion generation for collaborative robots and advanced scene flow estimation from LiDAR data. In her foundational 2017 work, Zhang developed a method for generating safe robot motions in dynamic environments by modulating dynamical systems using multiple depth sensors—a practical solution for enabling robots to adapt to unpredictable human movements in real time. Her more recent 2024 research tackles the challenging problem of scene flow estimation from sparse LiDAR point clouds, introducing a multiscale neighborhood cluster prior that significantly improves the accuracy of predicting 3D motion in autonomous driving and robotics applications. While her citation counts are still growing, reflecting the emerging nature of her research trajectory, Zhang’s work addresses fundamental challenges in making robots both safer and more perceptually capable. Her contributions are particularly relevant as the field moves toward deploying robots in unstructured, human-populated environments where real-time adaptability and robust 3D perception are essential.