Date of Award
3-10-2009
Document Type
Thesis
Degree Name
Master of Science
Department
Department of Systems Engineering and Management
First Advisor
David R. Jacques, PhD
Abstract
Secretary of Defense Robert M. Gates has emphasized a need for a greater number of intelligence, surveillance, and reconnaissance (ISR) assets to support combatant commanders and military operations globally. Unmanned systems, especially MAVs, used as ISR platforms provide the ability to maintain covertness during missions and help reduce the risk to human life. This research develops waypoint generation algorithms required to keep a point of interest (POI) in the field of view (FOV) of a fixed sensor on a micro air vehicle (MAV) in the presence of a constant wind.
Fixed sensors, while cheaper and less prone to mechanical failure than gimbaled sensors, provide challenges to keeping a POI in the FOV in the presence of wind since the MAV must adjust its attitude to maintain a desired flight path. As the vehicle adjusts its attitude, the POI may shift outside of the FOV. Wind affects MAVs more than other air vehicles because wind speeds can quickly approach the slow cruise speed of the vehicle.
This research builds upon previous work of maintaining a sensor aimpoint at a POI in the presence of wind. The algorithms establish waypoints at which a fixed sensor on a MAV at that waypoint points directly at the POI. As wind varies and the MAV does not perfectly reach each waypoint and attitude condition, the POI needs to remain in the FOV, ideally near the sensor aimpoint. Two scenarios are explored: one where the MAV orbits the POI, and the second where the MAV flies to align the sensor at the POI along a preferred look angle. The first scenario relies on a sensor aimed out the side of the MAV, while the second considers both a side-viewing sensor and a forward-viewing sensor. The research explored each scenario through hardware-in-the-loop testing as well as flight testing. The results indicate the algorithms keep the POI in the FOV at least 66% of the time as long as the wind speed was less than 25% of the cruise speed; at higher winds, the MAV has a difficult time tracking the flight path generated by the sensor aimpoint algorithm.
AFIT Designator
AFIT-GAE-ENV-09-M01
DTIC Accession Number
ADA495682
Recommended Citation
Farrell, Shannon M., "Waypoint Generation Based on Sensor Aimpoint" (2009). Theses and Dissertations. 2494.
https://scholar.afit.edu/etd/2494