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Proceedings Paper

New class of onboard absolute orientation measurement sensor for robotic mobile platforms
Author(s): Jahangir S Rastegar; Q. Jeffrey Ge; Carlos M. Pereira
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Paper Abstract

This paper presents new class sensors for onboard direct measurement of the angular orientation of robotic mobile platforms relative to a fixed or moving coordinate system. The currently available sensors are either based on inertia, vision or optical means to measure the angular orientation of an object. The inertial based devices, however, generally suffer from drift and noise. The vision systems and optical sensors generally have relatively short range and require line-of-sight access. The novel class of sensors presented in this paper are wireless, are in the form of waveguides that are illuminated by polarized Radio Frequency sources. A mobile robotic platform equipped with three or more of such waveguide sensors can determine its 3D orientation relative to the ground or other mobile robotic platforms. The 3D orientation sensors require very low power for operation, may be located at relatively far distances from the ground source or the illuminating mobile platform, and can operate while out of line-of-sight of the illuminating source. In this paper, the design, operation, algorithms for calculating 3D angular orientation from the sensor output, and a number of experimental results of sensor performance are presented. In addition, a discussion of the methods to increase the performance of the sensor system and other related issues are provided.

Paper Details

Date Published: 30 September 2003
PDF: 7 pages
Proc. SPIE 5267, Intelligent Robots and Computer Vision XXI: Algorithms, Techniques, and Active Vision, (30 September 2003); doi: 10.1117/12.515392
Show Author Affiliations
Jahangir S Rastegar, SUNY/Stony Brook (United States)
Q. Jeffrey Ge, SUNY/Stony Brook (United States)
Carlos M. Pereira, U.S. Army Tank-Automotive Research, Development and Engineering Ctr. (United States)


Published in SPIE Proceedings Vol. 5267:
Intelligent Robots and Computer Vision XXI: Algorithms, Techniques, and Active Vision
David P. Casasent; Ernest L. Hall; Juha Roning, Editor(s)

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