Papers
7
Total Citations
162
H-Index
5
About
Dr. L Chen is a leading researcher in robotics, with a primary focus on advancing the control and intelligence of industrial and redundant robotic systems. Their work is distinguished by the innovative fusion of machine learning with classical robotics theory to solve fundamental challenges in robot motion and interaction. A major contribution is the development of novel inverse kinematics (IK) solvers for redundant robots, including the deep-learning damped least squares method and the enhanced step-size Gaussian damped least squares method, which achieve high speed and precision. Dr. Chen has also made significant strides in robot-environment interaction, pioneering impedance sliding mode control with adaptive fuzzy compensation and finite-time control schemes to ensure stable and accurate force control under uncertain conditions. Their application of generalized frequency response functions with improved convolutional neural networks for fault diagnosis of heavy-duty industrial robots demonstrates a commitment to practical, real-world reliability. With their most-cited paper garnering 55 citations and a total of over 160 citations across their key works, Dr. Chen’s research is shaping the next generation of intelligent, safe, and high-performance robotic systems for complex industrial tasks.
Research Focus
Key Achievements
Top Papers
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- 5Impedance with Finite-Time Control Scheme for Robot-Environment Interaction11 citations · 2020
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