About

David W. Casbeer is a prominent researcher specializing in autonomous systems, unmanned aerial vehicles (UAVs), multi-agent coordination, and optimal control theory. His work sits at a compelling intersection of mathematical rigor and practical robotics, addressing some of the most pressing challenges in autonomous navigation and cooperative decision-making. Casbeer's most influential contributions include groundbreaking work on differential game theory, particularly his 2020 study on multi-player reach-avoid games in 3D space (80 citations), which provided complete strategic solutions for teams of autonomous aerial robots engaged in pursuit-evasion scenarios. His sustained investigation into Dubins path planning — producing both a widely cited 2017 paper on tight bounding methods (60 citations) and foundational 2016 work on lower and upper bounds — has meaningfully advanced how robots and UAVs compute efficient, curvature-constrained trajectories through sequential waypoints. Beyond theoretical contributions, Casbeer has tackled real-world applications including urban air mobility energy management, stochastic safe navigation, convoy support planning in degraded networks, and event-triggered distributed control for nonholonomic robot teams. His research reflects a consistent commitment to scalable, deployable solutions for complex multi-agent environments. With growing citation impact across a diverse body of work, Casbeer represents a distinctive voice bridging control theory, game theory, and autonomous systems engineering.

Research Focus

Key Achievements

7
H-Index
13
Papers
221
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
Optimal Strategies for a Class of Multi-Player Reach-Avoid Differential Games in 3D Space
80 citations · 2020
📈 Most Prolific Year: 2016 (3 Papers)
🤝 Key Collaborators: 17
🏛 Institutions: United States Air Force Research Laboratory, Wright-Patterson Air Force Base, U.S. Air Force Research Laboratory Aerospace Systems Directorate

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago