Organizational Unit:
Daniel Guggenheim School of Aerospace Engineering
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Feasibility Study to Determine the Economic and Operational Benefits of Utilizing Unmanned Aerial Vehicles (UAVs)
Development and Evaluation of an Automated Path Planning Aid
Flight Test Validation of a Neural Network based Long Term Learning Adaptive Flight Controller
Collaborative Search and Pursuit for Autonomous Helicopters
Flight Testing of Nap of-the-Earth Unmanned Helicopter Systems
Modeling Urban Environments for Communication-Aware UAV Swarm Path Planning
Terrain Height Evidence Sharing for Collaborative Autonomous Rotorcraft Operation
High Performance Nap-of-the-Earth Unmanned Helicopter Flight
Visual Marker Detection In The Presence Of Colored Noise for Unmanned Aerial Vehicles
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