Papers
71
Total Citations
1,149
H-Index
18
About
Lijin Fang is a robotics and control systems researcher whose work spans power transmission line inspection robotics, battery state estimation, and advanced control theory. Among his most influential contributions is his pioneering research on autonomous inspection robots for extra-high voltage power transmission lines, beginning as early as 2004, where he developed control systems capable of navigating complex overhead wire environments — work that has collectively garnered over 150 citations. Fang has made particularly significant strides in battery management, proposing increasingly sophisticated state-of-charge (SOC) estimation techniques using extended Kalman filters, sliding mode observers, unscented Kalman filters, and H∞ observers, with his 2011 paper alone accumulating 171 citations. These contributions directly address real-world challenges in autonomous mobile robot energy management. More recently, Fang has expanded into advanced control theory, publishing notable work on model-free finite-time terminal sliding mode control and disturbance observers for uncertain robotic systems. His 2023 work on RGB-D semantic segmentation signals a growing interest in deep learning-based perception. With over 600 cumulative citations, Fang's career reflects a productive evolution from applied robotics toward sophisticated estimation, control, and computer vision research.
Research Focus
Key Achievements
Top Papers
- 1
- 2Battery state estimation using Unscented Kalman Filter72 citations · 2009
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- 4A battery State of Charge estimation method with extended Kalman filter58 citations · 2008
- 5A battery state of charge estimation method using sliding mode observer55 citations · 2008
- 6
- 7Cross-modal attention fusion network for RGB-D semantic segmentation44 citations · 2023
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