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Map Building and Monte Carlo Localization Using Global Appearance of Omnidirectional Images
Departamento de Ingeniería de Sistemas Industriales , Universidad Miguel Hernández, Avda. de la Universidad s/n, 03202, Elche (Alicante), Spain
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Received: 30 September 2010; in revised form: 25 November 2010 / Accepted: 28 November 2010 / Published: 14 December 2010
Abstract: In this paper we deal with the problem of map building and localization of a mobile robot in an environment using the information provided by an omnidirectional vision sensor that is mounted on the robot. Our main objective consists of studying the feasibility of the techniques based in the global appearance of a set of omnidirectional images captured by this vision sensor to solve this problem. First, we study how to describe globally the visual information so that it represents correctly locations and the geometrical relationships between these locations. Then, we integrate this information using an approach based on a spring-mass-damper model, to create a topological map of the environment. Once the map is built, we propose the use of a Monte Carlo localization approach to estimate the most probable pose of the vision system and its trajectory within the map. We perform a comparison in terms of computational cost and error in localization. The experimental results we present have been obtained with real indoor omnidirectional images.
Keywords: global appearance; panoramic images; homomorphic filtering; Fourier Signature; topological mapping; monte-carlo localization
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Payá, L.; Fernández, L.; Gil, A.; Reinoso, O. Map Building and Monte Carlo Localization Using Global Appearance of Omnidirectional Images. Sensors 2010, 10, 11468-11497.
Payá L, Fernández L, Gil A, Reinoso O. Map Building and Monte Carlo Localization Using Global Appearance of Omnidirectional Images. Sensors. 2010; 10(12):11468-11497.
Payá, Luis; Fernández, Lorenzo; Gil, Arturo; Reinoso, Oscar. 2010. "Map Building and Monte Carlo Localization Using Global Appearance of Omnidirectional Images." Sensors 10, no. 12: 11468-11497.