Chao Huang

Tongji University, Beihang University

Papers

7

Total Citations

88

H-Index

6

About

Chao Huang is a leading researcher in multi-robot systems, cyber-physical security, and intelligent control, whose work bridges theoretical rigor with real-world robotic applications. His most impactful contribution lies in developing game-theoretic and self-learning frameworks for distributed task allocation and coalition formation under uncertainty—critical for deploying robots in hazardous environments. His 2023 paper on game-theoretical task allocation for multiple mobile robots (22 citations) and his 2024 work on self-learning coalition formation (14 citations) have set new standards for scalable, robust multi-robot coordination. In cyber-physical systems, Huang’s game-theoretic approach to optimal injection attacks (20 citations) provides a powerful framework for resource-constrained security, while his distributed localization algorithm using iterative learning (12 citations) addresses real-time positioning under imperfect communication. His earlier work on compliant joint actuators for lower-limb exoskeletons (8 citations) demonstrates his commitment to human-robot interaction. With over 88 total citations across his top papers, Huang’s research is widely recognized for advancing both the theoretical foundations and practical deployment of autonomous systems in safety-critical domains.

Research Focus

Key Achievements

6
H-Index
7
Papers
88
Total Citations
13
Avg Citations/Paper
🏆 Most Cited Paper
Task Allocation With Minimum Requirements for Multiple Mobile Robot Systems: A Game-Theoretical Approach
22 citations · 2023
📈 Most Prolific Year: 2022 (2 Papers)
🤝 Key Collaborators: 14
🏛 Institutions: Tongji University, Beihang University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago