Kaiser, Susanna (2020) Successive Collaborative SLAM: Towards Reliable Inertial Pedestrian Navigation. Information, 11 (464). Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/info11100464. ISSN 2078-2489.
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Kurzfassung
In emergency scenarios, such as a terrorist attack or a building on fire, it is desirable to track first responders in order to coordinate the operation. Pedestrian tracking methods solely based on inertial measurement units in indoor environments are candidates for such operations since they do not depend on pre-installed infrastructure. A very powerful indoor navigation method represents collaborative simultaneous localization and mapping (collaborative SLAM), where the learned maps of several users can be combined in order to help indoor positioning. In this paper, maps are estimated from several similar trajectories (multiple users) or one user wearing multiple sensors. They are combined successively in order to obtain a precise map and positioning. For reducing complexity, the trajectories are divided into small portions (sliding window technique) and are partly successively applied to the collaborative SLAM algorithm. We investigate successive combinations of the map portions of several pedestrians and analyze the resulting position accuracy. The results depend on several parameters, e.g., the number of users or sensors, the sensor drifts, the amount of revisited area, the number of iterations, and the windows size. We provide a discussion about the choice of the parameters. The results show that the mean position error can be reduced to ≈0.5 m when applying partly successive collaborative SLAM.
elib-URL des Eintrags: | https://elib.dlr.de/136590/ | ||||||||
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Dokumentart: | Zeitschriftenbeitrag | ||||||||
Titel: | Successive Collaborative SLAM: Towards Reliable Inertial Pedestrian Navigation | ||||||||
Autoren: |
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Datum: | 30 September 2020 | ||||||||
Erschienen in: | Information | ||||||||
Referierte Publikation: | Ja | ||||||||
Open Access: | Ja | ||||||||
Gold Open Access: | Ja | ||||||||
In SCOPUS: | Ja | ||||||||
In ISI Web of Science: | Ja | ||||||||
Band: | 11 | ||||||||
DOI: | 10.3390/info11100464 | ||||||||
Verlag: | Multidisciplinary Digital Publishing Institute (MDPI) | ||||||||
ISSN: | 2078-2489 | ||||||||
Status: | veröffentlicht | ||||||||
Stichwörter: | indoor navigation; pedestrian dead reckoning; simultaneous localization and mapping; FootSLAM; collaborative mapping; professional use cases | ||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||
HGF - Programm: | Verkehr | ||||||||
HGF - Programmthema: | Straßenverkehr | ||||||||
DLR - Schwerpunkt: | Verkehr | ||||||||
DLR - Forschungsgebiet: | V ST Straßenverkehr | ||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | V - NGC KoFiF (alt) | ||||||||
Standort: | Oberpfaffenhofen | ||||||||
Institute & Einrichtungen: | Institut für Kommunikation und Navigation > Nachrichtensysteme | ||||||||
Hinterlegt von: | Kaiser, Dr.-Ing. Susanna | ||||||||
Hinterlegt am: | 21 Okt 2020 12:24 | ||||||||
Letzte Änderung: | 25 Okt 2023 08:22 |
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