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Proceedings Paper

Aerial platform attitude measurement by artificial vision
Author(s): F. Truchetet; O. Aubreton; P. Gorria; O. Laligant
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Paper Abstract

Two measurement systems based on electronic imagers for attitude determination of light and low-cost airborne vectors in clear weather condition are presented. Both the devices are based on the following scheme: a binarized sky line image is selected as referential, then each shot, after binarization is segmented in two parts whose mean values are subtracted to the corresponding data computed from referential image. From this comparison analogical or digital values are deduced that give way to estimating the roll and pitch variation angles. The first system is made of off-the-shelf devices: black and white CMOS camera and processing unit made of a dedicated electronic. A second proposition is presented. It makes use of a CMOS retina, developed by our team, dedicated to real time, analogical intercorrelation computing. A simple external processing implemented in a microcontroller completes the system. A model for the embarked imaging system and an equation for an ideal horizon image with respect to rolling and pitch angles are proposed. The method for estimating these angles from the image and errors induced by the various approximations of the model are then presented. A series of experimental results obtained from real images confirms the previous propositions. The last section is dedicated to a presentation of the retinal imager solution, experimental results are also provided in this part.

Paper Details

Date Published: 2 February 2006
PDF: 12 pages
Proc. SPIE 6070, Machine Vision Applications in Industrial Inspection XIV, 60700D (2 February 2006); doi: 10.1117/12.642090
Show Author Affiliations
F. Truchetet, Le2i, UMR, CNRS 5158, Univ. de Bourgogne (France)
O. Aubreton, Le2i, UMR, CNRS 5158, Univ. de Bourgogne (France)
P. Gorria, Le2i, UMR, CNRS 5158, Univ. de Bourgogne (France)
O. Laligant, Le2i, UMR, CNRS 5158, Univ. de Bourgogne (France)


Published in SPIE Proceedings Vol. 6070:
Machine Vision Applications in Industrial Inspection XIV
Fabrice Meriaudeau; Kurt S. Niel, Editor(s)

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