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GPS-SLAM: An Augmentation of the ORB-SLAM Algorithm

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 m...

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Detalles Bibliográficos
Autores principales: Kiss-Illés, Dániel, Barrado, Cristina, Salamí, Esther
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6891537/
https://www.ncbi.nlm.nih.gov/pubmed/31731624
http://dx.doi.org/10.3390/s19224973
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author Kiss-Illés, Dániel
Barrado, Cristina
Salamí, Esther
author_facet Kiss-Illés, Dániel
Barrado, Cristina
Salamí, Esther
author_sort Kiss-Illés, Dániel
collection PubMed
description 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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spelling pubmed-68915372019-12-18 GPS-SLAM: An Augmentation of the ORB-SLAM Algorithm Kiss-Illés, Dániel Barrado, Cristina Salamí, Esther Sensors (Basel) Article 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. MDPI 2019-11-15 /pmc/articles/PMC6891537/ /pubmed/31731624 http://dx.doi.org/10.3390/s19224973 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kiss-Illés, Dániel
Barrado, Cristina
Salamí, Esther
GPS-SLAM: An Augmentation of the ORB-SLAM Algorithm
title GPS-SLAM: An Augmentation of the ORB-SLAM Algorithm
title_full GPS-SLAM: An Augmentation of the ORB-SLAM Algorithm
title_fullStr GPS-SLAM: An Augmentation of the ORB-SLAM Algorithm
title_full_unstemmed GPS-SLAM: An Augmentation of the ORB-SLAM Algorithm
title_short GPS-SLAM: An Augmentation of the ORB-SLAM Algorithm
title_sort gps-slam: an augmentation of the orb-slam algorithm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6891537/
https://www.ncbi.nlm.nih.gov/pubmed/31731624
http://dx.doi.org/10.3390/s19224973
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