One of the classical tasks of a mobile robot is building a map of its environment. This has led to a large body of work on the problem of simultaneous localization and mapping (SLAM). Traditionally, those maps are used mainly for navigation purposes, which only requires geometric information. However, more demanding applications of mobile robots (e. g., service or rescue robots) require semantically meaningful structures in the environment to be extracted, a process known as semantic mapping (Galindo, Fernandez-Madrigal, González and Saffiotti, 2008). Semantic maps can be useful for a variety of tasks, such as humanrobot communication or planning goal-directed interaction with objects in the environment.