A Virtual Sensor for Room Detection

P. Buschka and A. Saffiotti

Indoor environments typically consist of sets of connected room-like spaces. We present a local technique that uses range data to detect these spaces during navigation. Our technique includes two parts: segmentation, which isolates room-like spaces and detects when the robot has entered a new one; and feature extraction, which associates each space with a set of geometric features useful for navigation or recognition. Many such features can be considered: here we propose a new method to compute width and length of a rectangular room in a way which is largely invariant with respect to the configuration of the furniture. We report experimental results that show the performance of our technique, and hint at a possible use of this technique for coarse localization on a topological map.
P. Buschka and A. Saffiotti. A Virtual Sensor for Room Detection. Proc. of the IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), pp. 637-642. Lausanne, CH, 2002.
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