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Integrating Known Locations in FootSLAM and Investigating the Influence of Different Prior Information

Kaiser, Susanna (2017) Integrating Known Locations in FootSLAM and Investigating the Influence of Different Prior Information. In: 2017 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2017. 2017 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2017 (ISI/Scopus), 2017-09-18 - 2017-09-21, Sapporo, Japan. doi: 10.1109/IPIN.2017.8115938.

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Kurzfassung

Pedestrian positioning without receiving any GNSS signal or other reference signals as it might be the case in indoor environments or tunnels is still a challenging field of interest. In infrastructure-free approaches that are considered also for professional applications Inertial Measurement Units (IMUs) mounted on the foot or other parts of the body are commonly used. IMU based techniques still suffer from the remaining drift especially when the environment is unknown and not re-visited, or when the pedestrian walks randomly in large areas. In order to overcome this problem the so called FootSLAM algorithm, that is applied in this paper and performs already very good in buildings with restricted room sizes assuming re-visiting the area, is extended to handle known locations. FootSLAM is a SLAM (Simultaneous Localization and Mapping) algorithm estimating the map while walking wearing an inertial sensor on the foot or at other locations of the body. With the use of few known locations, the estimated FootSLAM map can be refined and re-used again for other users walking in that specific area. Beside the derivation of the algorithm handling known locations in FootSLAM, the influence of different kinds of prior knowledges on the FootSLAM algorithm is analyzed in this paper in terms of error and map quality performance.

elib-URL des Eintrags:https://elib.dlr.de/112893/
Dokumentart:Konferenzbeitrag (Vortrag)
Titel:Integrating Known Locations in FootSLAM and Investigating the Influence of Different Prior Information
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Kaiser, Susannasusanna.kaiser (at) dlr.dehttps://orcid.org/0000-0003-3210-6259NICHT SPEZIFIZIERT
Datum:19 September 2017
Erschienen in:2017 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2017
Referierte Publikation:Ja
Open Access:Nein
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Ja
DOI:10.1109/IPIN.2017.8115938
Name der Reihe:International Conference on Indoor Positioning and Indoor Navigation
Status:veröffentlicht
Stichwörter:pedestrian navigation; simultaneous localization and mapping (SLAM); indoor navigation; inertial navigation system;
Veranstaltungstitel:2017 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2017 (ISI/Scopus)
Veranstaltungsort:Sapporo, Japan
Veranstaltungsart:internationale Konferenz
Veranstaltungsbeginn:18 September 2017
Veranstaltungsende:21 September 2017
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Verkehr
HGF - Programmthema:Bodengebundener Verkehr (alt)
DLR - Schwerpunkt:Verkehr
DLR - Forschungsgebiet:V BF - Bodengebundene Fahrzeuge
DLR - Teilgebiet (Projekt, Vorhaben):V - Fahrzeugintelligenz (alt)
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Institut für Kommunikation und Navigation > Nachrichtensysteme
Hinterlegt von: Kaiser, Dr.-Ing. Susanna
Hinterlegt am:07 Jul 2017 11:17
Letzte Änderung:24 Apr 2024 20:17

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