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Quantifying the quality of indoor maps

Assali, M. ; Pipelidis, G. ; Podolskiy, V. ; Iwaszczuk, Dorota ; Heinen, L. ; Gerndt, M. (2019)
Quantifying the quality of indoor maps.
ISPRS Geospatial Week 2019. Enschede (10–14 June 2019)
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (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.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2019
Autor(en): Assali, M. ; Pipelidis, G. ; Podolskiy, V. ; Iwaszczuk, Dorota ; Heinen, L. ; Gerndt, M.
Art des Eintrags: Bibliographie
Titel: Quantifying the quality of indoor maps
Sprache: Englisch
Publikationsjahr: 5 Juni 2019
Ort: Enschede
Band einer Reihe: XLII-2/W13
Veranstaltungstitel: ISPRS Geospatial Week 2019
Veranstaltungsort: Enschede
Veranstaltungsdatum: 10–14 June 2019
URL / URN: https://doi.org/10.5194/isprs-archives-XLII-2-W13-739-2019
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Kurzbeschreibung (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.

Freie Schlagworte: Quality Metrics, Indoor Map, Robot Map, Dynamic Quality Assessment
Fachbereich(e)/-gebiet(e): 13 Fachbereich Bau- und Umweltingenieurwissenschaften
13 Fachbereich Bau- und Umweltingenieurwissenschaften > Institut für Geodäsie
13 Fachbereich Bau- und Umweltingenieurwissenschaften > Institut für Geodäsie > Fernerkundung und Bildanalyse
Hinterlegungsdatum: 04 Okt 2019 06:24
Letzte Änderung: 04 Okt 2019 06:24
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