Reference : Unmanned aerial vehicles UAVs attitude, height, motion estimation and control using v...
Scientific journals : Article
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/9960
Unmanned aerial vehicles UAVs attitude, height, motion estimation and control using visual systems
English
Mondragon, Ivan F. [Universidad Politecnica de Madrid (UPM) - Centro de Automatica y Robotica (CAR) > Computer Vision Group]
Olivares Mendez, Miguel Angel mailto [Universidad Politecnica de Madrid (UPM) - Centro de Automatica y Robotica (CAR) > Computer Vision Group]
Campoy, Pascual [Universidad Politecnica de Madrid (UPM) - Centro de Automatica y Robotica (CAR) > Computer Vision Group]
Martinez, Carol [Universidad Politecnica de Madrid (UPM) - Centro de Automatica y Robotica (CAR) > Computer Vision Group]
Mejias, Luis [Queensland University of Technology (QUT), Brisbane, Australia > Australian Research Center for Aerospace Automation]
2010
AUTONOMOUS ROBOTS
Springer
29
1
17-34
Yes (verified by ORBilu)
International
0929-5593
Dordrecht
[en] Omnidirectional images ; Catadioptric systems ; Stereo vision ; Unmanned aerial vehicles (UAV) ; Motion estimation ; Fuzzy control
[en] This paper presents an implementation of an aircraft pose and motion estimator using visual systems as the principal sensor for controlling an Unmanned Aerial Vehicle (UAV) or as a redundant system for an Inertial Measure Unit (IMU) and gyros sensors. First, we explore the applications of the unified theory for central catadioptric cameras for attitude and heading estimation, explaining how the skyline is projected on the catadioptric image and how it is segmented and used to calculate the UAV's attitude. Then we use appearance images to obtain a visual compass, and we calculate the relative rotation and heading of the aerial vehicle. Additionally, we show the use of a stereo system to calculate the aircraft height and to measure the UAV's motion. Finally, we present a visual tracking system based on Fuzzy controllers working in both a UAV and a camera pan and tilt platform. Every part is tested using the UAV COLIBRI platform to validate the different approaches, which include comparison of the estimated data with the inertial values measured onboard the helicopter platform and the validation of the tracking schemes on real flights.
Universidad Politecnica de Madrid and Comunidad Autonoma de Madrid ; Fondo Social Europeo (FSE) ; Spanish Science and Technology Ministry [2007-66156]
http://hdl.handle.net/10993/9960
10.1007/s10514-010-9183-2
The work reported in this paper is the conclusion of several research stages at the Computer Vision Group - Universidad Politecnica de Madrid. The authors would like to thank Jorge Leon for supporting the flight trials, the I. A. Institute - CSIC for collaborating in the flights, and the Universidad Politecnica de Madrid and Comunidad Autonoma de Madrid and Fondo Social Europeo (FSE) for the authors' Ph.D Scholarships. This work has been sponsored by the Spanish Science and Technology Ministry under the grant CICYTDPI 2007-66156.

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