title: Map building and monte carlo localization using global appearance of omnidirectional images.
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.
authors.affiliation: Departamento de Ingeniería de Sistemas Industriales, Universidad Miguel Hernández, Avda. de la Universidad s/n, 03202, Elche, Alicante, Spain. lpaya@umh.es
authors.forename: Luis
authors.initials: L
authors.lastname: Payá
authors.forename: Lorenzo
authors.initials: L
authors.lastname: Fernández
authors.forename: Arturo
authors.initials: A
authors.lastname: Gil
authors.forename: Oscar
authors.initials: O
authors.lastname: Reinoso
mesh_terms: D001108:Architecture / Q000295:instrumentation / Q000379:methods; D001185:Artificial Intelligence; D003198:Computer Simulation; D040362:Geographic Information Systems / Q000295:instrumentation; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D008377:Maps as Topic; D008954:Models, Biological; D008962:Models, Theoretical; D009010:Monte Carlo Method; D010363:Pattern Recognition, Automated / Q000379:methods / Q000706:statistics & numerical data; D012371:Robotics / Q000379:methods