Papers

28

Total Citations

708

H-Index

11

About

Anmin Zhu is a robotics and intelligent systems researcher whose work sits at the intersection of biologically inspired computing, autonomous navigation, and multi-robot coordination. Over two decades, he has made significant contributions to mobile robot navigation, developing novel approaches that draw on neural networks, fuzzy logic, and neurodynamics to enable robots to operate safely and efficiently in complex, dynamic environments. His 2011 paper on bioinspired neurodynamics-based tracking control (157 citations) demonstrated how biological neural principles could generate smooth, real-time velocity commands for nonholonomic robots — a critical advance for practical deployment. Complementing this, his neurofuzzy navigation framework (144 citations) elegantly unified sensor fusion with adaptive learning for obstacle avoidance and target seeking. Zhu has also been a leading voice in multi-robot systems, proposing self-organizing map (SOM)-based architectures for dynamic task assignment across both ground-level and three-dimensional swarm environments, accumulating over 200 citations in this thread of research alone. His work extends even into agricultural robotics, with a practical integrated gripper-cutter system for greenhouse harvesting. Collectively, Zhu's research portfolio reflects a consistent and impactful commitment to bridging theoretical intelligence models with real-world autonomous robotic systems.

Research Focus

Key Achievements

11
H-Index
28
Papers
708
Total Citations
25
Avg Citations/Paper
🏆 Most Cited Paper
A Bioinspired Neurodynamics-Based Approach to Tracking Control of Mobile Robots
157 citations · 2011
📈 Most Prolific Year: 2004 (4 Papers)
🤝 Key Collaborators: 21
🏛 Institutions: Shenzhen University, University of Guelph, University of Wisconsin–Madison

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8
  9. 9
  10. 10

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago