The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-2/W13
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W13, 739–745, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W13-739-2019
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W13, 739–745, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W13-739-2019

  05 Jun 2019

05 Jun 2019

QUANTIFYING THE QUALITY OF INDOOR MAPS

M. Assali1, G. Pipelidis2, V. Podolskiy1, D. Iwaszczuk3, L. Heinen4, and M. Gerndt1 M. Assali et al.
  • 1Chair of Computer Architecture and Parallel Systems, Dept. of Informatics, Technical University of Munich, Munich, Germany
  • 2Software and Systems Engineering Research Group, Dept. of Informatics, Technical University of Munich, Munich, Germany
  • 3Remote Sensing and Image Analysis Group, Dept. of Civil and Environmental Engineering Science, Technische Universität Darmstadt, Germany
  • 4BMW Group IT, Munich, Germany

Keywords: Quality Metrics, Indoor Map, Robot Map, Dynamic Quality Assessment

Abstract. Indoor maps are required for multiple applications, such as, navigation, building maintenance and robotics. One of common methods for map generation is laser scanning. In such maps, not only geometry of the map is of interest, but also its quality. This study aims at developing methods for real-time generation of indoor maps using features extracted from pointclouds obtained by a robot with their simultaneous quality assessment. We investigate, how this quality can be quantified for feature-based maps. First, we introduce a method for modeling 2D maps into 3D models that enable their usage for localization. Second, we review and evaluate a number of algorithms that can enable us to address features in a map. Hence, we enable the generation of objects from a pointcloud that has been sensed. Finally, we study several aspects of the map quality and we formalize them into metrics that can be applied to quantify their quality.