Rudol, Piotr 2011 (English)Licentiate thesis, monograph (Other academic)
The range of missions performed by Unmanned Aircraft Systems (UAS) has been steadily growing in the past decades thanks to continued development in several disciplines. The goal of increasing the autonomy of UAS's is widening the range of tasks which can be carried out without, or with minimal, external help. This thesis presents methods for increasing specific aspects of autonomy of UAS's operating both in outdoor and indoor environments where cameras are used as the primary sensors.
First, a method for fusing color and thermal images for object detection, geolocation and tracking for UAS's operating primarily outdoors is presented. Specifically, a method for building saliency maps where human body locations are marked as points of interest is described. Such maps can be used in emergency situations to increase the situational awareness of first responders or a robotic system itself. Additionally, the same method is applied to the problem of vehicle tracking. A generated stream of geographical locations of tracked vehicles increases situational awareness by allowing for qualitative reasoning about, for example, vehicles overtaking, entering or leaving crossings.
Second, two approaches to the UAS indoor localization problem in the absence of GPS-based positioning are presented. Both use cameras as the main sensors and enable autonomous indoor ight and navigation. The first approach takes advantage of cooperation with a ground robot to provide a UAS with its localization information. The second approach uses marker-based visual pose estimation where all computations are done onboard a small-scale aircraft which additionally increases its autonomy by not relying on external computational power.
Place, publisher, year, pages
Linköping: Linköping University Electronic Press, 2011. 96 p.
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1510
UAV, UAS, UAV autonomy, human-body detection, color-thermal image fusion, vehicle tracking, geolocation, UAV indoor navigation
National CategoryComputer Vision and Robotics (Autonomous Systems)
Identifiersurn:nbn:se:liu:diva-71295 (URN)LiU-Tek-Lic-2011:49 (Local ID)978-91-7393-034-5 (ISBN)oai:DiVA.org:liu-71295 (OAI)diva2:450766 (DiVA)
2011-11-04, Alan Turing, Hus E, Campus Valla, Linköpings universitet, Linköping, 13:15 (English)