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Path Markup Language for Indoor Navigation

Indoor navigation is critical in many tasks such as firefighting, emergency medical response, and SWAT response, where GPS signals are not available. Prevailing approaches such as beacons, radio signal triangulation, SLAM, and IMU methods are either expensive or impractical in extreme conditions, e....

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Autores principales: Cai, Yang, Alber, Florian, Hackett, Sean
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7304747/
http://dx.doi.org/10.1007/978-3-030-50436-6_25
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author Cai, Yang
Alber, Florian
Hackett, Sean
author_facet Cai, Yang
Alber, Florian
Hackett, Sean
author_sort Cai, Yang
collection PubMed
description Indoor navigation is critical in many tasks such as firefighting, emergency medical response, and SWAT response, where GPS signals are not available. Prevailing approaches such as beacons, radio signal triangulation, SLAM, and IMU methods are either expensive or impractical in extreme conditions, e.g. poor visibility and sensory drifting. In this study, we develop a path markup language for pre-planning routes and interacting with the user on a mobile device for real-time indoor navigation. The interactive map is annotated with walkable paths and landmarks that can be used for inertial motion sensor-based navigation. The wall-following and landmark-checking algorithms help to cancel drifting errors along the way. Our preliminary experiments show that the approach is affordable and efficient to generate annotated building floor path maps and it is feasible to use the map for indoor navigation in real-time on a mobile device with motion sensors. The method can be applied to intelligent helmets and mobile phones, including potential applications of first responders, tour guide for buildings, and assistance for visually impaired users.
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spelling pubmed-73047472020-06-22 Path Markup Language for Indoor Navigation Cai, Yang Alber, Florian Hackett, Sean Computational Science – ICCS 2020 Article Indoor navigation is critical in many tasks such as firefighting, emergency medical response, and SWAT response, where GPS signals are not available. Prevailing approaches such as beacons, radio signal triangulation, SLAM, and IMU methods are either expensive or impractical in extreme conditions, e.g. poor visibility and sensory drifting. In this study, we develop a path markup language for pre-planning routes and interacting with the user on a mobile device for real-time indoor navigation. The interactive map is annotated with walkable paths and landmarks that can be used for inertial motion sensor-based navigation. The wall-following and landmark-checking algorithms help to cancel drifting errors along the way. Our preliminary experiments show that the approach is affordable and efficient to generate annotated building floor path maps and it is feasible to use the map for indoor navigation in real-time on a mobile device with motion sensors. The method can be applied to intelligent helmets and mobile phones, including potential applications of first responders, tour guide for buildings, and assistance for visually impaired users. 2020-05-25 /pmc/articles/PMC7304747/ http://dx.doi.org/10.1007/978-3-030-50436-6_25 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Cai, Yang
Alber, Florian
Hackett, Sean
Path Markup Language for Indoor Navigation
title Path Markup Language for Indoor Navigation
title_full Path Markup Language for Indoor Navigation
title_fullStr Path Markup Language for Indoor Navigation
title_full_unstemmed Path Markup Language for Indoor Navigation
title_short Path Markup Language for Indoor Navigation
title_sort path markup language for indoor navigation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7304747/
http://dx.doi.org/10.1007/978-3-030-50436-6_25
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