Papers

75

Total Citations

1,091

H-Index

18

About

Byung-Cheol Min is a prolific robotics and artificial intelligence researcher whose work spans multi-robot systems, human-robot interaction, autonomous vehicles, and smart agricultural technologies. Best known for developing SMART-LLM (2024, 127 citations), a groundbreaking framework that leverages large language models for embodied multi-robot task planning, Min has consistently pushed the boundaries of intelligent autonomous systems. His research into multi-robot coordination is further demonstrated through foundational contributions to rendezvous strategies and network topology-based tracking, establishing theoretical and practical frameworks for decentralized robot teams. Min's interdisciplinary reach is notable: he has developed low-cost unmanned surface vehicles for real-time water quality monitoring (2019, 77 citations), advanced BIM-based construction robotics (2022, 67 citations), and applied precision technologies to dairy farming (2023, 55 citations). His work on cloud robotics, deep reinforcement learning-based computational offloading, and natural language communication models further reflects a commitment to making robots more capable and accessible in real-world environments. With research addressing multi-human multi-robot workload allocation and wireless relay deployment, Min's portfolio reveals a researcher dedicated to bridging theoretical rigor with transformative practical applications across diverse and challenging domains.

Research Focus

Key Achievements

18
H-Index
75
Papers
1,091
Total Citations
15
Avg Citations/Paper
🏆 Most Cited Paper
SMART-LLM: Smart Multi-Agent Robot Task Planning using Large Language Models
127 citations · 2024
📈 Most Prolific Year: 2024 (10 Papers)
🤝 Key Collaborators: 112
🏛 Institutions: Purdue University West Lafayette, Start Making A Reader Today, Carnegie Mellon University, Kyung Hee University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 34 days ago