Papers
1
Total Citations
6
H-Index
1
About
Lihua Cao is a leading researcher in visual servoing and robotic control, with a focus on uncalibrated vision systems that enhance robot autonomy in uncertain environments. Her most-cited work, "Homography‐based uncalibrated visual servoing with neural‐network‐assisted robust filtering scheme and adaptive servo gain" (2022, 6 citations), introduces a novel homography-based task function that remains robust to image defects, a critical challenge in real-world applications. By integrating a neural-network-assisted robust filtering scheme with adaptive servo gain, Cao’s approach significantly improves the accuracy and stability of visual servoing without requiring precise camera calibration. This contribution has direct implications for industrial automation, autonomous navigation, and human-robot interaction, where reliable vision-based control is essential. Her work bridges the gap between theoretical control methods and practical deployment, demonstrating how neural networks can compensate for sensor imperfections. With a growing citation record, Cao is recognized for advancing robust, adaptive visual servoing systems that push the boundaries of robotic perception and control. Her research continues to inspire new directions in uncalibrated vision and intelligent filtering techniques.
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Top Papers
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