Zhimin Han
Papers
4
Total Citations
35
H-Index
3
About
Zhimin Han is a leading researcher in multi-robot systems and nonlinear control, with a focus on distributed localization, formation control, and intelligent optimization. His work addresses fundamental challenges in enabling robot teams to operate autonomously under real-world constraints—such as limited sensing, switching communication topologies, and the absence of global positioning references. Han’s most cited paper (20 citations) introduces a novel nonlinear model predictive control framework that combines recurrent neural networks with differential evolution optimization for precise position control of flexible-joint robots, demonstrating a powerful synergy between learning and control. He has also made significant contributions to distributed localization, providing a necessary and sufficient geometric condition for triangular localizability in multi-robot systems, and to formation control under directed and switching topologies using only local relative measurements. His work on simultaneous estimation of position and orientation without a compass further advances the autonomy of robot swarms. With a growing citation impact and a clear focus on practical, scalable solutions, Han’s research is shaping the future of decentralized robotic coordination.
Research Focus
Key Achievements
Top Papers
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