Introduction
Building accurate maps of indoor environments is one of the typical problems in mobile robotics. In this task, a robot moves along a trajectory while gathering information with sensors. Typical maps represent the parts in the environment which are occupied by objects, as for example occupancy grid maps [5, 15]. The maps are then used for localization and navigation tasks. However, little work have been done to add semantic information to these maps. For a lot of applications, the service of robots can be improved if they are able to recognize places and differentiate them.
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Mozos, Ó.M. (2010). Semantic Learning of Places from Range Data. In: Semantic Labeling of Places with Mobile Robots. Springer Tracts in Advanced Robotics, vol 61. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11210-2_3
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