Papers
6
Total Citations
18
H-Index
3
About
Lile He is a robotics and control systems researcher whose work sits at the intersection of autonomous robot design, advanced control theory, and intelligent manufacturing. His research spans self-balancing robotic platforms, underwater robot control, and industrial automation, with a particular emphasis on developing sophisticated control algorithms that enhance robot stability, adaptability, and real-world performance. Among his most notable contributions is his work on two-wheeled self-balancing robots, where he has explored both mechanical design and novel control strategies, including adaptive fuzzy anti-integral saturation PID methods and reaction wheel mechanisms. He has also made meaningful advances in Model Predictive Control (MPC), proposing learning-based frameworks that integrate event-triggered mechanisms, self-tuning parameters, and basic-residual cooperative models to improve prediction accuracy and computational efficiency for mobile and underwater robotic systems. A particularly impactful applied contribution is his development of a robotic slag removal system for magnesium smelting, combining infrared sensing with Faster R-CNN to automate a hazardous industrial process. His papers have collectively accumulated citations across robotics, control engineering, and industrial automation communities. He represents a productive blend of theoretical rigor and practical engineering innovation, making his work valuable reading for researchers in intelligent robotics and autonomous control systems.
Research Focus
Key Achievements
Top Papers
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- 4A Novel Learning-Based MPC Method via Basic-Residual Cooperative Model2 citations · 2025
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