RFID autonomous robot for product inventory and location

A solution for the automation of inventory taking and location of prod-ucts in a store or warehouse is presented. Radio Frequency Identifica-tion (RFID), an automatic identification technology, and mobile robotics are combined in the design of an inventory robot. The navigation of the robot is comma...

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Detalhes bibliográficos
Autor: Morenza Cinos, Marc
Formato: tesis doctoral
Estado:Versión publicada
Fecha de publicación:2018
País:España
Recursos:CBUC, CESCA
Repositorio:TDR. Tesis Doctorales en Red
OAI Identifier:oai:www.tdx.cat:10803/664139
Acesso em linha:http://hdl.handle.net/10803/664139
Access Level:acceso abierto
Palavra-chave:Radio Frequency Identification (RFID)
Autonomous robotics
Inventory
Inventory Record Inaccuracy (IRI)
Product location
62
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spelling RFID autonomous robot for product inventory and locationMorenza Cinos, MarcRadio Frequency Identification (RFID)Autonomous roboticsInventoryInventory Record Inaccuracy (IRI)Product location62A solution for the automation of inventory taking and location of prod-ucts in a store or warehouse is presented. Radio Frequency Identifica-tion (RFID), an automatic identification technology, and mobile robotics are combined in the design of an inventory robot. The navigation of the robot is commanded by an algorithm that takes as input the progress of new identifications. Such algorithm is essential for the robot to deliver an accuracy higher than 99% and for an optimal inventory duration. An interface for the interaction with the robot and a set of procedures for its operation are implemented. The location of items is implemented using two different approaches. The first approach applies clustering to streams of identifications and assigns the known location of a reference item to all the members of a cluster. The second approach applies Bayesian Re-cursive Estimation after the computation of an identification model. A methodology for the assessment is proposed and the data set generated for the analysis shared openly. Inventory accuracy and location are as-sessed in real scenarios. The proposed solution is demonstrated valuable and ready for the market.Es presenta una solució per a l'automatizació de l'inventari i la localització dels productes de tendes i magatzems. Radio Frequecy Identification (RFID), una tecnologia d'identificació automàtica, i la robòtica mòbil es combinen per dissenyar un robot per a inventaris. La navegació del robot està comandada per un algoritme que escolta el progrés de les noves identificacions. L'algoritme és essencial per tal que el robot obtingui una exactitud superior al 99% i per tal que la duració de l'inventari sigui òptima. S'implementen una interfície d'interacció i el conjunt de procediments necessaris per a operar amb el robot. La localització dels productes s'aborda de dues maneres. La primera consisteix en aplicar clústering a les cadenes d'identificacions dels productes i després assignar la localitzacio coneguda d'un producte de referència a tots els membres del clúster. El segon mètode de localització consisteix en aplicar Bayesian Recursive Estimation després d'haver computat un model d'identificació. Es proposa una metodolgia per a l'avaluació dels inventaris i el dataset generat per a l'anàlisi és compartit obertament. L'exactitud dels inventaris i la localització s'avaluen en escenaris reals. Es demostra que la solució proposada és de valor i està llesta per entrar al mercat.Programa de doctorat en Tecnologies de la Informació i les ComunicacionsUniversitat Pompeu FabraPous Andrés, RafaelUniversitat Pompeu Fabra. Departament de Tecnologies de la Informació i les Comunicacions201820202018info:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/publishedVersion172 p.application/pdfapplication/pdfhttp://hdl.handle.net/10803/664139TDX (Tesis Doctorals en Xarxa)reponame:TDR. Tesis Doctorales en Redinstname:CBUC, CESCAInglésL'accés als continguts d'aquesta tesi queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons: http://creativecommons.org/licenses/by-nc-sa/4.0/http://creativecommons.org/licenses/by-nc-sa/4.0/info:eu-repo/semantics/openAccessoai:www.tdx.cat:10803/6641392026-06-14T12:46:07Z
dc.title.none.fl_str_mv RFID autonomous robot for product inventory and location
title RFID autonomous robot for product inventory and location
spellingShingle RFID autonomous robot for product inventory and location
Morenza Cinos, Marc
Radio Frequency Identification (RFID)
Autonomous robotics
Inventory
Inventory Record Inaccuracy (IRI)
Product location
62
title_short RFID autonomous robot for product inventory and location
title_full RFID autonomous robot for product inventory and location
title_fullStr RFID autonomous robot for product inventory and location
title_full_unstemmed RFID autonomous robot for product inventory and location
title_sort RFID autonomous robot for product inventory and location
dc.creator.none.fl_str_mv Morenza Cinos, Marc
author Morenza Cinos, Marc
author_facet Morenza Cinos, Marc
author_role author
dc.contributor.none.fl_str_mv Pous Andrés, Rafael
Universitat Pompeu Fabra. Departament de Tecnologies de la Informació i les Comunicacions
dc.subject.none.fl_str_mv Radio Frequency Identification (RFID)
Autonomous robotics
Inventory
Inventory Record Inaccuracy (IRI)
Product location
62
topic Radio Frequency Identification (RFID)
Autonomous robotics
Inventory
Inventory Record Inaccuracy (IRI)
Product location
62
description A solution for the automation of inventory taking and location of prod-ucts in a store or warehouse is presented. Radio Frequency Identifica-tion (RFID), an automatic identification technology, and mobile robotics are combined in the design of an inventory robot. The navigation of the robot is commanded by an algorithm that takes as input the progress of new identifications. Such algorithm is essential for the robot to deliver an accuracy higher than 99% and for an optimal inventory duration. An interface for the interaction with the robot and a set of procedures for its operation are implemented. The location of items is implemented using two different approaches. The first approach applies clustering to streams of identifications and assigns the known location of a reference item to all the members of a cluster. The second approach applies Bayesian Re-cursive Estimation after the computation of an identification model. A methodology for the assessment is proposed and the data set generated for the analysis shared openly. Inventory accuracy and location are as-sessed in real scenarios. The proposed solution is demonstrated valuable and ready for the market.
publishDate 2018
dc.date.none.fl_str_mv 2018
2018
2020
dc.type.none.fl_str_mv info:eu-repo/semantics/doctoralThesis
info:eu-repo/semantics/publishedVersion
format doctoralThesis
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10803/664139
url http://hdl.handle.net/10803/664139
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 172 p.
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Universitat Pompeu Fabra
publisher.none.fl_str_mv Universitat Pompeu Fabra
dc.source.none.fl_str_mv TDX (Tesis Doctorals en Xarxa)
reponame:TDR. Tesis Doctorales en Red
instname:CBUC, CESCA
instname_str CBUC, CESCA
reponame_str TDR. Tesis Doctorales en Red
collection TDR. Tesis Doctorales en Red
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300724

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