About

Min Keng Tan is a robotics and intelligent systems researcher whose work spans multi-robot coordination, motion control, neural network optimization, and autonomous navigation. With a career stretching from foundational biomimetic robotics to sophisticated multi-agent systems, Tan has made lasting contributions to the field of robotic intelligence and control. His most influential work, "Multicriteria Optimization for Coordination of Redundant Robots Using a Dual Neural Network" (2009, 113 citations), introduced a groundbreaking neural-network-based framework for coordinating kinematically redundant multi-robot systems, generalizing prior single-robot performance criteria into a powerful multicriteria formulation. Complementing this, his backstepping-based trajectory tracking algorithm for closed-chain five-bar robots (2012, 83 citations) demonstrated elegant integration of approximation methods with mechanical design principles. Tan's research breadth is equally impressive — from pioneering biomimetic robot fish motion control and underwater sensor network architectures to RSSI-based wireless navigation and human-robot interaction through bimodal intent inference. His later work on hierarchical task allocation and ant colony optimization for swarm robotics reflects a sustained commitment to scalable, resource-aware multi-robot systems. Collectively, his publications have accumulated hundreds of citations, cementing his reputation as a versatile and impactful contributor to modern robotics research.

Research Focus

Key Achievements

8
H-Index
17
Papers
347
Total Citations
20
Avg Citations/Paper
🏆 Most Cited Paper
Multicriteria Optimization for Coordination of Redundant Robots Using a Dual Neural Network
113 citations · 2009
📈 Most Prolific Year: 2009 (2 Papers)
🤝 Key Collaborators: 44
🏛 Institutions: Shandong Institute of Automation, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Universiti of Malaysia Sabah

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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