Papers
10
Total Citations
114
H-Index
5
About
Qun Lu is a robotics and control systems researcher whose work spans mobile robot navigation, visual servoing, formation control, and emerging applications in miniature soft robotics. His most significant contributions center on wheeled mobile robots (WMRs), where he has developed sophisticated control frameworks that address real-world challenges including unknown skidding and slipping, model uncertainties, input disturbances, and torque saturation. His 2020 paper on posture control with dynamic obstacle avoidance—his most cited work with 50 citations—combines nonlinear model predictive control with robust disturbance handling, representing a notable advance in constrained robot navigation. Lu has also made meaningful strides in visual servoing, proposing adaptive and switching-based controllers that enable mobile robots to perform simultaneous tracking and regulation without precise camera calibration. His 2019 work on distributed leader-follower formation control demonstrates his broader interest in multi-robot coordination. More recently, Lu has extended his expertise to magnetic miniature soft robots, exploring path tracking control strategies with promising biomedical implications for targeted therapy and drug delivery. Across his portfolio, Lu consistently bridges theoretical rigor with practical applicability, making his research valuable to both control theorists and robotics engineers.
Research Focus
Key Achievements
Top Papers
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- 3Distributed Leader-follower Formation Control of Nonholonomic Mobile Robots14 citations · 2019
- 4Adaptive Visual Regulation of Wheeled Mobile Robots: a Switching Approach10 citations · 2019
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