Yandong Luo
Papers
4
Total Citations
34
H-Index
3
About
Yandong Luo’s research lies at the intersection of swarm robotics, bio-inspired algorithms, and intelligent fault diagnosis. His major contributions focus on enabling autonomous robot swarms to perform complex tasks—such as target search and path formation—under realistic constraints like limited communication and decentralized control. Notably, Luo drew inspiration from the slime mould *Physarum polycephalum* to develop a self-organizing exploration strategy for path formation, demonstrating how biological principles can yield efficient, decentralized network solutions. His work on robot chains with elimination mechanisms addresses the critical challenge of cooperative search in communication-constrained environments, advancing practical swarm deployment. In industrial applications, Luo pioneered the use of extreme learning machines optimized by a level-based learning swarm optimizer for fault diagnosis of robot reducers, achieving faster computation without sacrificing accuracy. With his most-cited paper garnering 16 citations, Luo’s research is steadily gaining recognition for bridging theoretical bio-inspired design with real-world robotics and manufacturing needs. His contributions offer valuable frameworks for students and researchers interested in swarm intelligence, autonomous systems, and intelligent maintenance.
Research Focus
Key Achievements
Top Papers
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- 4Robot Chain Based Self-organizing Search Method of Swarm Robotics2 citations · 2018