Intelligent Routing and Coordination for Unmanned Aerial Systems

This project trains a machine learning model to generate fast, safe obstacle-avoidance flight routes for unmanned aircraft, replacing a current routing system too slow for dynamic airspace conditions. Students will build a 3D simulation environment, generate training data via path-planning algorithms, and train a model optimized for safety, fuel efficiency, and waypoint compliance, with routes validated against the legacy tool. If progress allows, the project will extend to multi-aircraft formation flight, coordinating 2–3 aircraft to maintain relative navigation and formation integrity during maneuvers.