Paper
24 January 2011 An embedded omnidirectional vision navigator for automatic guided vehicles
Author Affiliations +
Proceedings Volume 7878, Intelligent Robots and Computer Vision XXVIII: Algorithms and Techniques; 78780N (2011) https://doi.org/10.1117/12.872281
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States
Abstract
Omnidirectional vision appears the definite significance since its advantage of acquiring full 360° horizontal field of vision information simultaneously. In this paper, an embedded original omnidirectional vision navigator (EOVN) based on fish-eye lens and embedded technology has been researched. Fish-eye lens is one of the special ways to establish omnidirectional vision. However, it appears with an unavoidable inherent and enormous distortion. A unique integrated navigation method which is conducted on the basis of targets tracking has been proposed. It is composed of multi-target recognition and tracking, distortion rectification, spatial location and navigation control. It is called RTRLN. In order to adapt to the different indoor and outdoor navigation environments, we implant mean-shift and dynamic threshold adjustment into the Particle Filter algorithm to improve the efficiency and robustness of tracking capability. RTRLN has been implanted in an independent development embedded platform. EOVN likes a smart crammer based on COMS+FPGA+DSP. It can guide various vehicles in outdoor environments by tracking the diverse marks hanging in the air. The experiments prove that the EOVN is particularly suitable for the guidance applications which need high requirements on precision and repeatability. The research achievements have a good actual applied inspection.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Weijia Feng, Baofeng Zhang, Juha Röning, Zuoliang Cao, and Xiaoning Zong "An embedded omnidirectional vision navigator for automatic guided vehicles", Proc. SPIE 7878, Intelligent Robots and Computer Vision XXVIII: Algorithms and Techniques, 78780N (24 January 2011); https://doi.org/10.1117/12.872281
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Cited by 4 scholarly publications.
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KEYWORDS
Detection and tracking algorithms

Particles

Image processing

Distortion

Particle filters

Digital signal processing

Navigation systems

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