Haibing Guan

Shanghai Jiao Tong University

Papers

11

Total Citations

168

H-Index

7

About

Haibing Guan is a robotics researcher whose work centers on multi-robot systems, swarm intelligence, and autonomous exploration — areas where coordinating teams of robots to accomplish complex tasks efficiently remains a central challenge. Drawing heavily from bio-inspired computation, Guan has made notable contributions by adapting Particle Swarm Optimization (PSO) to real-world robotic scenarios, developing algorithms that enable robot teams to explore unknown environments, form patterns, and locate targets without relying on centralized control or precise global information. His most influential work, "Frontier-based multi-robot map exploration using Particle Swarm Optimization" (2011), has garnered 59 citations and demonstrates how PSO-driven strategies can significantly improve collaborative mapping efficiency. Complementing this, his PSO-inspired search algorithm (32 citations) extends these principles to target-finding tasks under realistic, information-limited conditions. Across his broader portfolio, Guan consistently champions distributed, decentralized approaches — including auction-based coordination, virtual pheromone mechanisms, and timer-driven aggregation — that scale well with larger robot swarms. His collective body of work, totaling over 160 citations, reflects a sustained commitment to bridging theoretical swarm intelligence with practical multi-robot applications, making his research particularly valuable for students and engineers working at the intersection of artificial intelligence and autonomous systems.

Research Focus

Key Achievements

7
H-Index
11
Papers
168
Total Citations
15
Avg Citations/Paper
🏆 Most Cited Paper
Frontier-based multi-robot map exploration using Particle Swarm Optimization
59 citations · 2011
📈 Most Prolific Year: 2009 (5 Papers)
🤝 Key Collaborators: 17
🏛 Institutions: Shanghai Jiao Tong University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago