This paper describes an idea for determining self-organization using visual land marks. 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 5.4 centimeters in less than 0.3 second. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Kim, Y. S., Kim, J. C., Park, E. J., & Lee, J. (2006). Vision-based self-localization of autonomous guided vehicle using landmarks of colored pentagons. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4291 LNCS-I, pp. 133–140). Springer Verlag. https://doi.org/10.1007/11919476_14
Mendeley helps you to discover research relevant for your work.