NDLI: Automatically calibrating the viewing direction of optic-flow sensors

Content Provider	IEEE Xplore Digital Library
Author	Briod, A. Zufferey, J. Floreano, D.
Copyright Year	2012
Description	Author affiliation: Laboratory of Intelligent Systems, Ecole Polytechnique Fédérale de Lausanne, 1015, Switzerland (Briod, A.; Zufferey, J.; Floreano, D.)
Abstract	Because of their low weight, cost and energy consumption, optic-flow sensors attract growing interest in robotics for tasks such as self-motion estimation or depth measurement. Most applications require a large number of these sensors, which involves a fair amount of calibration work for each setup. In particular, the viewing direction of each sensor has to be measured for proper operation. This task is often cumbersome and prone to errors, and has to be carried out every time the setup is slightly modified. This paper proposes an algorithm for viewing direction calibration relying on rate gyroscope readings and a recursive weighted linear least square estimation of the rotation matrix elements. The method only requires the user to realize random rotational motions of its setup by hand. The algorithm provides hints about the current precision of the estimation and what motions should be performed to improve it. To assess the validity of the method, tests were performed on an experimental setup and the results compared to a precise manual calibration. The repeatability of the gyroscope-based calibration process reached ±1.7° per axis.
Starting Page	3956
Ending Page	3961
File Size	1793999
Page Count	6
File Format	PDF
ISBN	9781467314039
ISSN	10504729
e-ISBN	9781467314053
e-ISBN	9781467314046
DOI	10.1109/ICRA.2012.6225011
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-05-14
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Optical sensors Optical imaging Calibration Adaptive optics Optical variables measurement Image sensors
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software

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