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One of the main research areas in robotics is navigating autonomously through
the environment. Although this problem has been solved in different manners using
highly demanding metric approaches that require multi-sensor data fusion, the topological
paradigm is a more natural and compact solution that scales better with the size of the
environment. Vision has always been regarded as the ideal sensor technology and several
methods have been proposed in the literature using cameras, but they are either timeconsuming,
require plenty of different sensors, or are very sensitive to illumination changes
in the environment, all of which limit their application scope.
This paper presents a fast-to-compute and moderately light-insensitive procedure based
exclusively on monocular images, capable of recognizing places in indoor and structured
outdoor environments by means of the identification of dominant vertical lines, local color
histograms, and a reduced number of blob features. The results show that the proposed
method provides good estimates of the current position in a first-location problem given a
single image. Therefore, it seems a promising technique for topological navigation, where
the succession of similar images supplies additional information.
Director: Álvaro Sánchez Miralles Autor: Jaime Boal Lugar: Aula de Seminarios Añadir a agenda electrónica: 
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