Estimation of Visual Maps with a Robot Network Equipped with Vision Sensors
AbstractIn 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.
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Gil, A.; Reinoso, Ó.; Ballesta, M.; Juliá, M.; Payá, L. Estimation of Visual Maps with a Robot Network Equipped with Vision Sensors. Sensors 2010, 10, 5209-5232.
Gil A, Reinoso Ó, Ballesta M, Juliá M, Payá L. Estimation of Visual Maps with a Robot Network Equipped with Vision Sensors. Sensors. 2010; 10(5):5209-5232.Chicago/Turabian Style
Gil, Arturo; Reinoso, Óscar; Ballesta, Mónica; Juliá, Miguel; Payá, Luis. 2010. "Estimation of Visual Maps with a Robot Network Equipped with Vision Sensors." Sensors 10, no. 5: 5209-5232.