Papers
6
Total Citations
83
H-Index
4
About
Lingyan Hu is a robotics researcher whose work centers on intelligent control, robotic manipulation, and vision-guided automation. Her most impactful contribution is an adaptive path-following controller for multijoint snake robots, which uses an improved Serpenoid curve to achieve precise trajectory tracking—a paper that has garnered 45 citations. She has also advanced robust control theory by developing a second-order adaptive integral terminal sliding mode approach for robotic manipulators, addressing trajectory tracking under uncertainties. In applied robotics, Hu has tackled the critical challenge of dynamic parameter identification for 6R robotic arms, using improved particle swarm optimization to enhance control precision. Her work extends to agricultural automation, where she developed YOLOv5s-Cherry for cherry target detection in dense scenes, and to industrial assembly, proposing a pose estimation method combining PnP algorithms with contour depth extraction for peg-in-hole tasks. Additionally, she has explored human-robot interaction, developing variable impedance control strategies that learn from demonstration trajectories. With over 80 citations across her publications, Hu’s research bridges theoretical control advances with practical robotic applications, making her work relevant to both academic researchers and engineers developing next-generation autonomous systems.
Research Focus
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Top Papers
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