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Micro unmanned aerial vehicle visual servoing for cooperative indoor exploration
2008 (English)In: Proceedings of the IEEE Aerospace Conference, IEEE conference proceedings, 2008Conference paper (Refereed)
Abstract [en]

Recent advances in the field of micro unmanned aerial vehicles (MAVs) make flying robots of small dimensions suitable platforms for performing advanced indoor missions. In order to achieve autonomous indoor flight a pose estimation technique is necessary. This paper presents a complete system which incorporates a vision-based pose estimation method to allow a MAV to navigate in indoor environments in cooperation with a ground robot. The pose estimation technique uses a lightweight light emitting diode (LED) cube structure as a pattern attached to a MAV. The pattern is observed by a ground robot's camera which provides the flying robot with the estimate of its pose. The system is not confined to a single location and allows for cooperative exploration of unknown environments. It is suitable for performing missions of a search and rescue nature where a MAV extends the range of sensors of the ground robot. The performance of the pose estimation technique and the complete system is presented and experimental flights of a vertical take-off and landing (VTOL) MAV are described.

Aerospace Conference Proceedings, ISSN 1095-323X ; 2008
National Category
Computer Science
URN: urn:nbn:se:liu:diva-40869DOI: 10.1109/AERO.2008.4526558Local ID: 54437ISBN: 978-1-4244-1487-1OAI: diva2:261718
The IEEE Aerospace Conference, March 1-8, Big Sky, Montana, USA
Available from2009-10-10 Created:2009-10-10 Last updated:2011-11-28Bibliographically approved
In thesis
1. Increasing Autonomy of Unmanned Aircraft Systems Through the Use of Imaging Sensors
Open this publication in new window or tab >>Increasing Autonomy of Unmanned Aircraft Systems Through the Use of Imaging Sensors
2011 (English)Licentiate thesis, monograph (Other academic)
Abstract [en]

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.

Publisher, range
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 Category
Computer Vision and Robotics (Autonomous Systems)
urn:nbn:se:liu:diva-71295 (URN)LiU-Tek-Lic-2011:49 (Local ID)978-91-7393-034-5 (ISBN)LiU-Tek-Lic-2011:49 (Archive number)LiU-Tek-Lic-2011:49 (OAI)
2011-11-04, Alan Turing, Hus E, Campus Valla, Linköpings universitet, Linköping, 13:15 (English)
Available from2011-11-28 Created:2011-10-10 Last updated:2011-11-28Bibliographically approved

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