ROBOT SELF-LOCALIZATION - Using Omni-directional Histogram Correlation

William F. Wood, Arthur T. Bradley, Samuel A. Miller, Nathanael A. Miller

Abstract

In this paper, we describe a robot self-localization algorithm that uses statistical measures to determine color space histograms correlations. The approach has been shown to work well in environments where spatial nodes have unique visual characteristics, including rooms, hallways, and outdoor locations. A full color omni-directional camera was used to capture images for this localization work. Images were processed using user-created algorithms in National Instrument’s LabView software development environment.

References

  1. Ulrich, I., Nourbakhsh, I. “Appearance-Based Place Recognization for Topological Localization”, IEEE International Conference on Robotics and Automation, April 2000, pp. 1023-1029.
  2. Papoulis, A., Pillai, S. Probability, Random Variable and Stochastic Processes, New York, NY: McGraw-Hill, 2002, ch. 8.
  3. Abe, Y., Shikano, M., Fukuda, T., Arai, F., and Tanaka, Y., “Vision Based Navigation System for Autonomous Mobile Robot with Global Matching”, IEEE International Conference on Robotics and Automation, May 1999, pp. 1299-1304.
  4. Kuipers, B.J., “Modeling spatial knowledge,” Cognitive Science, vol. 2, no. 2, pp. 129-153, 1978.
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Paper Citation


in Harvard Style

Wood W., Bradley A., Miller S. and Miller N. (2009). ROBOT SELF-LOCALIZATION - Using Omni-directional Histogram Correlation . In - ICINCO, ISBN , pages 0-0


in Bibtex Style

@conference{icinco09,
author={William F. Wood and Arthur T. Bradley and Samuel A. Miller and Nathanael A. Miller},
title={ROBOT SELF-LOCALIZATION - Using Omni-directional Histogram Correlation},
booktitle={ - ICINCO,},
year={2009},
pages={},
publisher={SciTePress},
organization={INSTICC},
doi={},
isbn={},
}


in EndNote Style

TY - CONF
JO - - ICINCO,
TI - ROBOT SELF-LOCALIZATION - Using Omni-directional Histogram Correlation
SN -
AU - Wood W.
AU - Bradley A.
AU - Miller S.
AU - Miller N.
PY - 2009
SP - 0
EP - 0
DO -