Donald H. Costello

United States Naval Academy

Papers

3

Total Citations

19

H-Index

3

About

Donald H. Costello is a leading researcher advancing autonomous systems for naval aviation, with a focus on computer vision, uncertainty quantification, and airworthiness certification. His work directly supports the U.S. Navy’s push toward uncrewed aircraft and reduced RF signatures. In his most-cited paper (2024, 8 citations), Costello introduced a probabilistic method for 3D object tracking using binocular cameras, incorporating quantified camera uncertainty to enhance tracking reliability in GPS-denied environments. His 2023 paper (6 citations) pioneered the use of industrial robotics and motion capture to automatically generate ground-truth image labels, solving a critical bottleneck in training deep neural networks for autonomous carrier-based aircraft. Costello also co-authored the 2022 National Airworthiness Council AI Working Group summit proceedings (5 citations), which established foundational airworthiness guidelines for AI-enabled uncrewed systems operating in contested airspace. By bridging computer vision, machine learning, and defense certification standards, Costello’s research provides the technical and regulatory framework needed to safely integrate autonomous aircraft into carrier operations, directly impacting the future of naval aviation.

Research Focus

Key Achievements

3
H-Index
3
Papers
19
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Probabilistic Object Tracking Using Quantified Camera Uncertainty Parameters in a Binocular System
8 citations · 2024
📈 Most Prolific Year: 2023 (2 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: United States Naval Academy

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago