Guozeng Cui
Papers
4
Total Citations
45
H-Index
3
About
Guozeng Cui is a leading researcher in the intersection of robotics, control theory, and artificial intelligence, with a primary focus on advancing autonomous systems in complex, uncertain environments. His work spans three critical domains: semantic visual SLAM for indoor robotics, consensus control for multi-agent systems, and adaptive control for robotic manipulators. Cui’s most impactful contribution is his pioneering approach to indoor 3D semantic robot VSLAM, where he integrated Mask R-CNN to overcome low label classification accuracy and sparse feature points—a solution that has garnered 21 citations and set a new standard for environmental mapping. He further advanced the field with a proportional integral observer-based consensus control method for discrete-time multi-agent systems (15 citations), enabling robust coordination among autonomous agents. In his recent work, Cui developed a finite-time command filtered adaptive control algorithm for robot manipulators operating in random vibration environments (8 citations), addressing parameter uncertainty and input saturation. His latest 2025 study on adaptive predefined-time optimal tracking control for flexible-joint robots demonstrates his ongoing commitment to pushing the boundaries of precision and efficiency in robotic systems.
Research Focus
Key Achievements
Top Papers
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