title: Estimation of visual maps with a robot network equipped with vision sensors.
abstract: In this paper we present an approach to the Simultaneous Localization and Mapping (SLAM) problem using a team of autonomous vehicles equipped with vision sensors. The SLAM problem considers the case in which a mobile robot is equipped with a particular sensor, moves along the environment, obtains measurements with its sensors and uses them to construct a model of the space where it evolves. In this paper we focus on the case where several robots, each equipped with its own sensor, are distributed in a network and view the space from different vantage points. In particular, each robot is equipped with a stereo camera that allow the robots to extract visual landmarks and obtain relative measurements to them. We propose an algorithm that uses the measurements obtained by the robots to build a single accurate map of the environment. The map is represented by the three-dimensional position of the visual landmarks. In addition, we consider that each landmark is accompanied by a visual descriptor that encodes its visual appearance. The solution is based on a Rao-Blackwellized particle filter that estimates the paths of the robots and the position of the visual landmarks. The validity of our proposal is demonstrated by means of experiments with a team of real robots in a office-like indoor environment.
authors.affiliation: Universidad Miguel Hernández, Avda. de la Universidad s/n, Ed. Quorum V, r03202 Elche, Alicante, Spain. arturo.gil@umh.es
authors.forename: Arturo
authors.initials: A
authors.lastname: Gil
authors.forename: Óscar
authors.initials: Ó
authors.lastname: Reinoso
authors.forename: Mónica
authors.initials: M
authors.lastname: Ballesta
authors.forename: Miguel
authors.initials: M
authors.lastname: Juliá
authors.forename: Luis
authors.initials: L
authors.lastname: Payá