Floor plan-free particle filter for indoor positioning of industrial vehicles

Bibliographic Details
Main Author: Silva, Ivo Miguel Menezes
Publication Date: 2020
Other Authors: Moreira, Adriano, Nicolau, Maria João, Pendão, Cristiano Gonçalves
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/1822/70557
Summary: Industry 4.0 is triggering the rapid development of solutions for indoor localization of industrial ve- hicles in the factories of the future. Either to support indoor navigation or to improve the operations of the factory, the localization of industrial vehicles imposes demanding requirements such as high accuracy, coverage of the entire operating area, low convergence time and high reliability. Industrial vehicles can be located using Wi-Fi fingerprinting, although with large positioning errors. In addition, these vehicles may be tracked with motion sensors, however an initial position is necessary and these sensors often suffer from cumulative errors (e.g. drift in the heading). To overcome these problems, we propose an indoor positioning system (IPS) based on a particle filter that combines Wi-Fi fingerprinting with data from motion sensors (displacement and heading). Wi-Fi position estimates are obtained using a novel approach, which explores signal strength measurements from multiple Wi-Fi interfaces. This IPS is capable of locating a vehicle prototype without prior knowledge of the starting position and heading, without depending on the building’s floor plan. An average positioning error of 0.74 m was achieved in performed tests in a factory-like building.
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spelling Floor plan-free particle filter for indoor positioning of industrial vehiclesIndoor positioningParticle filterWi-Fi fingerprintingSensor fusionIndustrial vehiclesEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e InformáticaIndustry 4.0 is triggering the rapid development of solutions for indoor localization of industrial ve- hicles in the factories of the future. Either to support indoor navigation or to improve the operations of the factory, the localization of industrial vehicles imposes demanding requirements such as high accuracy, coverage of the entire operating area, low convergence time and high reliability. Industrial vehicles can be located using Wi-Fi fingerprinting, although with large positioning errors. In addition, these vehicles may be tracked with motion sensors, however an initial position is necessary and these sensors often suffer from cumulative errors (e.g. drift in the heading). To overcome these problems, we propose an indoor positioning system (IPS) based on a particle filter that combines Wi-Fi fingerprinting with data from motion sensors (displacement and heading). Wi-Fi position estimates are obtained using a novel approach, which explores signal strength measurements from multiple Wi-Fi interfaces. This IPS is capable of locating a vehicle prototype without prior knowledge of the starting position and heading, without depending on the building’s floor plan. An average positioning error of 0.74 m was achieved in performed tests in a factory-like building.FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020, the PhD fellowship PD/BD/137401/2018 and the Technological Development in the scope of the projects in co-promotion no 002814/2015 (iFACTORY 2015-2018)CEUR-WsUniversidade do MinhoSilva, Ivo Miguel MenezesMoreira, AdrianoNicolau, Maria JoãoPendão, Cristiano Gonçalves2020-06-022020-06-02T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/1822/70557engIvo Silva, Adriano Moreira, Maria João Nicolau, Cristiano Pendão, “Floor Plan-free Particle Filter for Indoor Positioning of Industrial Vehicles”, in proceedings of the International Conference on Localization and GNSS, ICL-GNSS 2020, 2-4 June, Tampere, Finland (online), 2020, Volume 2626, ISSN: 1613-00731613-0073http://ceur-ws.org/Vol-2626/paper2.pdfinfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T04:45:16Zoai:repositorium.sdum.uminho.pt:1822/70557Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T14:57:30.352667Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Floor plan-free particle filter for indoor positioning of industrial vehicles
title Floor plan-free particle filter for indoor positioning of industrial vehicles
spellingShingle Floor plan-free particle filter for indoor positioning of industrial vehicles
Silva, Ivo Miguel Menezes
Indoor positioning
Particle filter
Wi-Fi fingerprinting
Sensor fusion
Industrial vehicles
Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
title_short Floor plan-free particle filter for indoor positioning of industrial vehicles
title_full Floor plan-free particle filter for indoor positioning of industrial vehicles
title_fullStr Floor plan-free particle filter for indoor positioning of industrial vehicles
title_full_unstemmed Floor plan-free particle filter for indoor positioning of industrial vehicles
title_sort Floor plan-free particle filter for indoor positioning of industrial vehicles
author Silva, Ivo Miguel Menezes
author_facet Silva, Ivo Miguel Menezes
Moreira, Adriano
Nicolau, Maria João
Pendão, Cristiano Gonçalves
author_role author
author2 Moreira, Adriano
Nicolau, Maria João
Pendão, Cristiano Gonçalves
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Silva, Ivo Miguel Menezes
Moreira, Adriano
Nicolau, Maria João
Pendão, Cristiano Gonçalves
dc.subject.por.fl_str_mv Indoor positioning
Particle filter
Wi-Fi fingerprinting
Sensor fusion
Industrial vehicles
Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
topic Indoor positioning
Particle filter
Wi-Fi fingerprinting
Sensor fusion
Industrial vehicles
Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
description Industry 4.0 is triggering the rapid development of solutions for indoor localization of industrial ve- hicles in the factories of the future. Either to support indoor navigation or to improve the operations of the factory, the localization of industrial vehicles imposes demanding requirements such as high accuracy, coverage of the entire operating area, low convergence time and high reliability. Industrial vehicles can be located using Wi-Fi fingerprinting, although with large positioning errors. In addition, these vehicles may be tracked with motion sensors, however an initial position is necessary and these sensors often suffer from cumulative errors (e.g. drift in the heading). To overcome these problems, we propose an indoor positioning system (IPS) based on a particle filter that combines Wi-Fi fingerprinting with data from motion sensors (displacement and heading). Wi-Fi position estimates are obtained using a novel approach, which explores signal strength measurements from multiple Wi-Fi interfaces. This IPS is capable of locating a vehicle prototype without prior knowledge of the starting position and heading, without depending on the building’s floor plan. An average positioning error of 0.74 m was achieved in performed tests in a factory-like building.
publishDate 2020
dc.date.none.fl_str_mv 2020-06-02
2020-06-02T00:00:00Z
dc.type.driver.fl_str_mv conference paper
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1822/70557
url http://hdl.handle.net/1822/70557
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Ivo Silva, Adriano Moreira, Maria João Nicolau, Cristiano Pendão, “Floor Plan-free Particle Filter for Indoor Positioning of Industrial Vehicles”, in proceedings of the International Conference on Localization and GNSS, ICL-GNSS 2020, 2-4 June, Tampere, Finland (online), 2020, Volume 2626, ISSN: 1613-0073
1613-0073
http://ceur-ws.org/Vol-2626/paper2.pdf
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv CEUR-Ws
publisher.none.fl_str_mv CEUR-Ws
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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