Unmanned aerial vehicles UAVs attitude, height, motion estimation and control using visual systems

Authors:
Iván F. Mondragón;Miguel A. Olivares-Méndez;Pascual Campoy;Carol Martínez;Luís Mejias
Affiliations:
Computer Vision Group U.P.M., Madrid, Spain 28006;Computer Vision Group U.P.M., Madrid, Spain 28006;Computer Vision Group U.P.M., Madrid, Spain 28006;Computer Vision Group U.P.M., Madrid, Spain 28006;Australian Research Centre for Aerospace Automation (ARCAA), School of Engineering Systems, Queensland University of Technology, Brisbane, Australia 4000
Venue:
Autonomous Robots
Year:
2010

Citing 13
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Abstract

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.