Qinghe Wu
Papers
11
Total Citations
93
H-Index
4
About
Qinghe Wu is a robotics and control systems researcher whose work centers on autonomous mobile robot navigation, multi-agent coordination, and intelligent control strategies. With a career spanning over a decade, Wu has made significant contributions to the design and optimization of controllers for nonholonomic wheeled mobile robots (WMRs), particularly in the challenging domains of trajectory tracking and obstacle avoidance. Wu's most impactful work explores advanced control methodologies, including fuzzy logic PD controllers and genetic algorithm-optimized PID controllers for autonomous robot trajectory tracking — earning 33 and 30 citations respectively, representing the core of his recognized scholarship. His research demonstrates a consistent drive to improve tracking accuracy while minimizing error in real-world robotic platforms such as the Quanser Qbot. Beyond single-robot systems, Wu has extensively investigated multi-robot formation control, applying techniques such as Model Predictive Control (MPC), sliding mode control (SMC), H∞ robustness frameworks, and particle swarm optimization to address communication failures and coordinated navigation challenges. More recently, his interests have extended to probabilistic motion planning for underwater robots operating under environmental uncertainty. Wu's body of work reflects a rigorous, interdisciplinary approach bridging classical control theory with modern computational intelligence for next-generation autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 4Control and Obstacle Avoidance of Wheeled Mobile Robot5 citations · 2015
- 5Coordination Control of Wheeled Mobile Robot Using MPC4 citations · 2015
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