Miniature air vehicles (MAVs) have attracted a large amount of interest recently both from the research community and from the public. New battery technologies as well as rapid developments in embedded processing and MEMS sensor technologies have greatly increased the potential of these vehicles. MAVs have been envisioned playing significant roles in both civil and military applications. Examples include: fire monitoring, search and rescue, traffic monitoring, crop monitoring, convoy protection, border surveillance, troop support, law enforcement, natural disaster relief, and aerial photography. The application of MAVs tends to center on the ability of the MAV to collect and deliver visual information to the user. In many applications it is important to be able to accurately geolocate items of interest in the visual data. However, the inaccuracies associated with MAV platforms have led to relatively large errors in previous attempts at geolocation. The first half of this thesis focuses on increasing the accuracy of geolocation estimates achievable using a hand-launchable MAV. To accomplish this, methods are presented for bias estimation, wind estimation, recursive least squares filtering, and optimal flight path generation. Hardware results are presented which demonstrate the ability to consistently localize targets to within 5 m regardless of wind conditions. The second half of this thesis focuses on using the high accuracy geolocation estimates to complete a search and engage mission. This is a mission in which the MAV not only locates the target, but also accurately delivers a payload to the target site. The focus is on delivering an attached payload via accurate landing at the target site. A vision-based landing approach is presented which is robust to both wind and moving targets. Simulation results are presented which demonstrate the effectiveness of the control.



College and Department

Ira A. Fulton College of Engineering and Technology; Mechanical Engineering



Date Submitted


Document Type





uav, mav, geolocation, geo-location, vision, guidance, landing