Vision-Based Self-Localization of Autonomous Guided Vehicle Using Landmarks of Colored Pentagons


The KIPS Transactions:PartB , Vol. 12, No. 4, pp. 387-394, Aug. 2005
10.3745/KIPSTB.2005.12.4.387,   PDF Download:

Abstract

This paper describes an idea for determining self-localization using visual landmark. The critical geometric dimensions of a pentagon are used here to locate the relative position of the mobile robot with respect to the pattern. This method has the advantages of simplicity and flexibility. This pentagon is also provided with a unique identification, using invariant features and colors that enable the system to find the absolute location of the patterns. This algorithm determines both the correspondence between observed landmarks and a stored sequence, computes the absolute location of the observer using those correspondences, and calculates relative position from a pentagon using its five vertices. The algorithm has been implemented and tested. In several trials it computes location accurate to within 5 centimeters in less than 0.3 second.


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Cite this article
[IEEE Style]
Y. S. Kim, E. J. Park, J. C. Kim, J. W. Lee, "Vision-Based Self-Localization of Autonomous Guided Vehicle Using Landmarks of Colored Pentagons," The KIPS Transactions:PartB , vol. 12, no. 4, pp. 387-394, 2005. DOI: 10.3745/KIPSTB.2005.12.4.387.

[ACM Style]
Young Sam Kim, Eun Jong Park, Joon Choel Kim, and Joon Whoan Lee. 2005. Vision-Based Self-Localization of Autonomous Guided Vehicle Using Landmarks of Colored Pentagons. The KIPS Transactions:PartB , 12, 4, (2005), 387-394. DOI: 10.3745/KIPSTB.2005.12.4.387.