Papers
5
Total Citations
123
H-Index
3
About
Qingcheng Chen is a leading researcher in robotics, specializing in the kinematics, dynamics, and control of robotic systems, with a particular focus on serial manipulators and lower extremity exoskeletons. His major contributions include developing an improved inverse kinematics algorithm using screw theory for a six-DOF robot manipulator, which significantly enhanced computational efficiency over traditional Denavit-Hartenberg methods. Chen has also pioneered human–robot cooperation controllers for lower extremity exoskeletons, employing nonlinear sliding mode control and radial basis function neural networks to improve tracking performance and reduce interaction forces. His work on single-input adaptive fuzzy sliding mode control further advanced exoskeleton technology by enabling intuitive shadowing of wearer motion with minimal force. With over 120 citations across his most-cited papers, Chen’s research has had a notable impact on industrial automation and assistive robotics. His innovative integration of screw theory with Kane’s equations for dynamic modeling has simplified complex analyses, while his exploration of uncalibrated visual servoing for welding robots highlights his versatility. Chen’s achievements underscore his role in advancing efficient, human-centric robotic systems for real-world applications.
Research Focus
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