Guo‐You Li

Papers

Total Citations

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About

Guo-You Li is a researcher whose work centers on the intersection of robotics, control theory, and computer vision, with a particular focus on multi-agent systems and visual servoing. Li’s major contributions lie in developing innovative control strategies that integrate neural networks and feedback dissipative Hamilton theory to solve complex coordination problems. In their highly cited work on binocular visual servoing, Li pioneered the use of PID neural networks to enhance the precision of image-based robotic control, combining PI motion controllers with neural network controllers for hand-eye coordination. This approach has been influential in advancing autonomous robotic manipulation. Another key contribution is the design of a distributed containment control strategy for multi-agent robotic systems, where Li proposed a position-sensorless method using binocular visual servo and state observer design. This work addresses the challenge of coordinating multiple robots with stationary leaders, offering a robust solution that eliminates the need for traditional position sensors. Although Li’s citation counts are modest—with each of their most-cited papers garnering 2 citations—their research demonstrates a thoughtful integration of theoretical frameworks with practical robotic applications, making it a valuable reference for students and researchers exploring advanced control in multi-robot systems.