Papers

3

Total Citations

17

H-Index

2

About

Jinqiang Hu is a researcher at the forefront of swarm robotics, specializing in bio-inspired cooperative control and complex area coverage. His work bridges biological intelligence and engineering, most notably through a novel swarm intelligence labour division approach that solves intricate area coverage problems involving nonlinear boundaries and forbidden zones. By integrating grid discretization with adaptive task allocation, Hu’s method enables robot swarms to efficiently map and navigate hazardous or irregular environments—a critical capability for disaster response and autonomous exploration. His seminal paper on this topic has garnered 11 citations, underscoring its influence in the field. Hu further expands the theoretical foundation of swarm robotics with his exploration of wolf pack intelligence, translating collective hunting strategies into robust cooperative control algorithms. This work, published in 2021, has already attracted 4 citations, highlighting its growing relevance. Through these contributions, Hu not only advances the practical deployment of multi-robot systems but also deepens our understanding of how natural swarm behaviors can inspire resilient, decentralized solutions for real-world challenges.

Research Focus

Key Achievements

2
H-Index
3
Papers
17
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
A swarm intelligence labour division approach to solving complex area coverage problems of swarm robots
11 citations · 2020
📈 Most Prolific Year: 2020 (2 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Chinese People's Armed Police Force Engineering University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago