Projects
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ML-HYDRAS: Machine Learning-Hydrodynamic Driven Rapid Assessment of Storms
Lincoln Laboratory's ML-HYDRAS tool will help users plan flood mitigation measures, model damage and debris flow, and prioritize resource allocation before, during, and after emergencies.
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Underwater PB&J: Combining Diver and Robot Strengths for Optimized Mid-Mission Teaming
New navigation and vehicle autonomy algorithms consider which tasks humans and autonomous systems respectively do best, with the goal of improving search path planning and object classification in underwater environments.
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Virtual Test Environments for UAVs
For experiments with unmanned aerial vehicles, researchers use simulated geographies that avoid the risks of real-world flight tests.
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