Real-Time Flight Path Optimization for Tracking Stop-And-Go Targets with Micro Air Vehicles

This research effort focuses on using a heuristic approach to determine the optimal flight path required to put an Unmanned Aircraft System's (UAS) sensor on a moving target in the presence of a constant wind field. This thesis builds on past work using dynamic optimization techniques to calculate minimum time to target. The computationally intensive dynamic optimization routines in their current form take a prohibitive amount of time to calculate and ultimately result in erroneous flight path predictions due to inherent execution time latencies. Therefore an iterative, suboptimal heuristic approach was explored to mitigate excessive calculation times and ultimately yield improved flight path predictions. This report not only explores the heuristic techniques used for flight path calculation, but also includes real world application and flight test results in a Micro Air Vehicle equipped with an autopilot.