Guodong Liu

Jiangnan University, North University of China

Papers

Total Citations

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About

Guodong Liu is a robotics researcher whose work spans visual servoing, pipeline inspection, human-robot interaction, and 3D simultaneous localization and mapping (SLAM). His most-cited paper, "Quasi-min-max model predictive control for image-based visual servoing" (2012, 9 citations), introduces a novel IBVS controller that uses tensor-product model transformation to handle image Jacobian uncertainties—a key contribution to vision-based robot control. In pipeline robotics, Liu developed a tracked in-pipe robot with a threaded nut mechanism and preload spring for diameter adjustment, analyzing its obstacle-crossing performance (2025, 3 citations), which addresses practical challenges in oil and gas infrastructure maintenance. He also advanced human-robot interaction through a multilayer hidden Markov models method for continuous gesture recognition (2013, 3 citations), enabling more natural robot communication. Additionally, his work on 3D visual SLAM using multiple iterative closest point (2015, 2 citations) improves data association in RGB-D sensors, enhancing robot navigation in unknown environments. Liu’s contributions demonstrate a strong focus on integrating control theory, perception, and mechanical design to solve real-world robotics problems, from factory floors to underground pipelines.