Lijing Li

Institute of Optics and Electronics, Chinese Academy of Sciences, China University of Mining and Technology

Papers

Total Citations

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About

Lijing Li is a leading researcher in autonomous vehicle control and sensor fusion, with a focus on enhancing the performance of small-scale robotic systems. Her work addresses critical challenges in path tracking and orientation estimation, particularly for resource-constrained platforms. Li's most cited paper (41 citations) introduces a cascaded NTSM-PID control method for four-wheel independently driven skid steer robotic vehicles, enabling precise path tracking without relying on high-performance processors or extensive sensor arrays—a breakthrough for compact, low-power applications. Her second notable contribution (19 citations) presents a multi-kernel maximum correntropy Kalman filter for inertial measurement units, significantly improving orientation accuracy under external acceleration and magnetic disturbances. This work has broad implications for human motion animation, rehabilitation robotics, and aerospace. Li's research bridges theoretical control design with practical deployment, demonstrating how advanced algorithms can overcome hardware limitations. Her achievements highlight a commitment to robust, real-world solutions in robotics and navigation, making her work essential reading for students and researchers tackling autonomy in constrained environments.