Kevin Leahy

MIT Lincoln Laboratory, Boston University

Papers

10

Total Citations

159

H-Index

7

About

Kevin Leahy’s research lies at the intersection of robotics, formal methods, and multi-agent coordination, with a central focus on enabling heterogeneous teams of robots to execute complex, high-level tasks under real-world constraints. His major contributions include the development of scalable and robust algorithms for task-based coordination from high-level specifications, as seen in his most-cited work, "Scalable and Robust Algorithms for Task-Based Coordination From High-Level Specifications (ScRATCHeS)" (58 citations). Leahy pioneered the use of temporal logic—such as Gaussian Distribution Temporal Logic (GDTL) and Capability Temporal Logic (CaTL)—to synthesize control policies that account for uncertainty, intertask dependencies, and strict deadlines. His work on control in belief space with temporal logic specifications (32 citations) and distributed information gathering under temporal logic constraints (16 citations) has advanced the field of autonomous systems operating in GPS-deprived or uncertain environments. Notably, his end-to-end framework for vision-based localization and mapping (16 citations) demonstrates practical applications for aerial-ground robot teams. Leahy’s research has been recognized for its impact on swarm control, informative path planning, and verification of autonomous systems, making him a leading voice in ensuring reliable, mission-critical robot coordination.

Research Focus

Key Achievements

7
H-Index
10
Papers
159
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
Scalable and Robust Algorithms for Task-Based Coordination From High-Level Specifications (ScRATCHeS)
58 citations · 2021
📈 Most Prolific Year: 2021 (2 Papers)
🤝 Key Collaborators: 16
🏛 Institutions: MIT Lincoln Laboratory, Boston University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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