Papers
2
Total Citations
13
H-Index
2
About
Dr. Ming Yuan is a leading researcher in multi-robot systems and intelligent optimization algorithms, with a focus on solving complex coordination and planning problems. His major contributions include the development of a novel Explosive Immune Evolutionary Algorithm (EIGA) for task allocation in multi-robot systems, which dramatically improves optimization speed by rapidly expanding population diversity through an explosive evolutionary mode. This work, published in 2012, has garnered 10 citations and remains a foundational approach for distributed robot coordination. Dr. Yuan also pioneered a chaotic small-world algorithm that integrates chaos optimization and information entropy to enhance robot path planning, achieving superior performance over conventional small-world methods. This 2012 study, with 3 citations, demonstrates his innovative use of chaotic dynamics for robotic navigation. By merging principles from immunology, chaos theory, and small-world networks, Dr. Yuan has advanced the efficiency and adaptability of autonomous robotic systems. His research is particularly valuable for students and engineers working on swarm robotics, evolutionary computation, and real-time path planning in dynamic environments.
Research Focus
Key Achievements
Top Papers
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