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GPS-SLAM: An augmentation of the ORB-SLAM algorithm

Kiss-Illés, Dániel; Barrado, C.; Salamí, E.

Abstract:
This work presents Global Positioning System-Simultaneous Localization and Mapping (GPS-SLAM), an augmented version of Oriented FAST (Features from accelerated segment test) and Rotated BRIEF (Binary Robust Independent Elementary Features) feature detector (ORB)-SLAM using GPS and inertial data to make the algorithm capable of dealing with low frame rate datasets. In general, SLAM systems are successful in case of datasets with a high frame rate. This work was motivated by a scarce dataset where ORB-SLAM often loses track because of the lack of continuity. The main work includes the determination of the next frame’s pose based on the GPS and inertial data. The results show that this additional information makes the algorithm more robust. As many large, outdoor unmanned aerial vehicle (UAV) flights save the GPS and inertial measurement unit (IMU) data of the capturing of images, this program gives an option to use the SLAM algorithm successfully even if the dataset has a low frame rate.

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Verlagsausgabe §
DOI: 10.5445/IR/1000104244
Veröffentlicht am 16.12.2019
Originalveröffentlichung
DOI: 10.3390/s19224973
Scopus
Zitationen: 3
Web of Science
Zitationen: 1
Dimensions
Zitationen: 2
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Arbeitswissenschaft und Betriebsorganisation (IFAB)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2019
Sprache Englisch
Identifikator ISSN: 1424-8220
KITopen-ID: 1000104244
Erschienen in Sensors
Verlag MDPI
Band 19
Heft 22
Seiten Art.-Nr.: 4973
Schlagwörter SLAM; GPS data; inertial; UAV; scarce dataset
Nachgewiesen in Dimensions
Web of Science
Scopus
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