Papers

5

Total Citations

199

H-Index

4

About

Michael J. Kuhlman is a leading researcher in multi-robot systems, specializing in task allocation and communication under extreme constraints. His most impactful work tackles the challenge of coordinating robot teams when communication is unreliable or limited—a critical problem for real-world deployments in disaster zones, underground environments, or space. Kuhlman’s landmark 2019 paper, "Auctions for multi-robot task allocation in communication limited environments," has garnered 154 citations, establishing a foundation for robust auction-based algorithms like the Sequential, Parallel, and G-Prim Auctions that function effectively even with lossy channels. Earlier, he advanced practical sensing for miniature robotics, developing compact distance sensors using Time Difference of Arrival (TDOA) and Received Signal Strength Indicator (RSSI), enabling precise inter-robot localization on resource-constrained platforms. His work on mixed-signal architectures for randomized receding horizon control further addresses the unique control challenges of miniature robots with strict power and size limits. Kuhlman’s contributions bridge theoretical algorithm design with hardware-constrained implementation, providing essential tools for resilient, scalable multi-robot coordination in the most demanding environments.

Research Focus

Key Achievements

4
H-Index
5
Papers
199
Total Citations
40
Avg Citations/Paper
🏆 Most Cited Paper
Auctions for multi-robot task allocation in communication limited environments
154 citations · 2019
📈 Most Prolific Year: 2012 (2 Papers)
🤝 Key Collaborators: 12
🏛 Institutions: United States Naval Research Laboratory, University of Maryland, College Park

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago