Semantic Localization of a Robot in a Real Home

In social robotics, it is important that a mobile robot knows where it is because it provides a starting point for other activities such as moving from one room to another. As a contribution to solving this problem in the field of the semantic location of the mobile robot, we pro- pose to implement...

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Hlavní autor: Bauer, Zuria (author)
Další autoři: Rangel, José Carlos (author), Cazorla, Miguel (author), Gomez Donoso, Francisco (author)
Médium: article
Jazyk:angličtina
Vydáno: 2020
Témata:
On-line přístup:https://link.springer.com/chapter/10.1007/978-3-319-99885-5_1
https://ridda2.utp.ac.pa/handle/123456789/9446
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author Bauer, Zuria
author2 Rangel, José Carlos
Cazorla, Miguel
Gomez Donoso, Francisco
author2_role author
author
author
author_browse Bauer, Zuria
Cazorla, Miguel
Gomez Donoso, Francisco
Rangel, José Carlos
author_facet Bauer, Zuria
Rangel, José Carlos
Cazorla, Miguel
Gomez Donoso, Francisco
author_role author
collection Repositorio Institucional de documento digitales de acceso abierto de la UTP
dc.creator.none.fl_str_mv Bauer, Zuria
Rangel, José Carlos
Cazorla, Miguel
Gomez Donoso, Francisco
dc.date.none.fl_str_mv 11/21/2018
11/21/2018
2020-01-06T14:31:20Z
2020-01-06T14:31:20Z
2020-01-06T14:31:20Z
2020-01-06T14:31:20Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv https://link.springer.com/chapter/10.1007/978-3-319-99885-5_1
https://ridda2.utp.ac.pa/handle/123456789/9446
https://ridda2.utp.ac.pa/handle/123456789/9446
dc.language.none.fl_str_mv eng
eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/embargoedAccess
dc.source.none.fl_str_mv reponame:Repositorio Institucional de documento digitales de acceso abierto de la UTP
instname:Universidad Tecnológica de Panamá
instacron:U Tecnológica de Panamá
dc.subject.none.fl_str_mv Robotics
Deep learning
Semantic localization
CNN training
Neural networks
Robotics
Deep learning
Semantic localization
CNN training
Neural networks
dc.title.none.fl_str_mv Semantic Localization of a Robot in a Real Home
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
description In social robotics, it is important that a mobile robot knows where it is because it provides a starting point for other activities such as moving from one room to another. As a contribution to solving this problem in the field of the semantic location of the mobile robot, we pro- pose to implement a methodology of recognition and scene learning in a real domestic environment. For this purpose, we used images from five different residences to create a dataset with which the base model was trained. The effectiveness of the implemented base model is evaluated in different scenarios. When the accuracy of the site identification decreases, the user provides feedback to the robot so that it can process the information collected from the new environment and re-identify the current location. The results obtained reinforce the need to acquire more knowledge when the environment is not recognizable by the pre-trained model.
eu_rights_str_mv embargoedAccess
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instacron_str U Tecnológica de Panamá
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instname_str Universidad Tecnológica de Panamá
language eng
network_acronym_str lrtest
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oai_identifier_str oai:ridda2.utp.ac.pa:123456789/9446
publishDate 2020
publishDateSort 2020
reponame_str Repositorio Institucional de documento digitales de acceso abierto de la UTP
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spelling Semantic Localization of a Robot in a Real HomeBauer, ZuriaRangel, José CarlosCazorla, MiguelGomez Donoso, FranciscoRoboticsDeep learningSemantic localizationCNN trainingNeural networksRoboticsDeep learningSemantic localizationCNN trainingNeural networksIn social robotics, it is important that a mobile robot knows where it is because it provides a starting point for other activities such as moving from one room to another. As a contribution to solving this problem in the field of the semantic location of the mobile robot, we pro- pose to implement a methodology of recognition and scene learning in a real domestic environment. For this purpose, we used images from five different residences to create a dataset with which the base model was trained. The effectiveness of the implemented base model is evaluated in different scenarios. When the accuracy of the site identification decreases, the user provides feedback to the robot so that it can process the information collected from the new environment and re-identify the current location. The results obtained reinforce the need to acquire more knowledge when the environment is not recognizable by the pre-trained model.In social robotics, it is important that a mobile robot knows where it is because it provides a starting point for other activities such as moving from one room to another. As a contribution to solving this problem in the field of the semantic location of the mobile robot, we pro- pose to implement a methodology of recognition and scene learning in a real domestic environment. For this purpose, we used images from five different residences to create a dataset with which the base model was trained. The effectiveness of the implemented base model is evaluated in different scenarios. When the accuracy of the site identification decreases, the user provides feedback to the robot so that it can process the information collected from the new environment and re-identify the current location. The results obtained reinforce the need to acquire more knowledge when the environment is not recognizable by the pre-trained model.2020-01-06T14:31:20Z2020-01-06T14:31:20Z2020-01-06T14:31:20Z2020-01-06T14:31:20Z11/21/201811/21/2018info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://link.springer.com/chapter/10.1007/978-3-319-99885-5_1https://ridda2.utp.ac.pa/handle/123456789/9446https://ridda2.utp.ac.pa/handle/123456789/9446engenginfo:eu-repo/semantics/embargoedAccessreponame:Repositorio Institucional de documento digitales de acceso abierto de la UTPinstname:Universidad Tecnológica de Panamáinstacron:U Tecnológica de Panamáoai:ridda2.utp.ac.pa:123456789/94462021-07-06T15:35:10Z
spellingShingle Semantic Localization of a Robot in a Real Home
Bauer, Zuria
Robotics
Deep learning
Semantic localization
CNN training
Neural networks
Robotics
Deep learning
Semantic localization
CNN training
Neural networks
status_str publishedVersion
title Semantic Localization of a Robot in a Real Home
title_full Semantic Localization of a Robot in a Real Home
title_fullStr Semantic Localization of a Robot in a Real Home
title_full_unstemmed Semantic Localization of a Robot in a Real Home
title_short Semantic Localization of a Robot in a Real Home
title_sort Semantic Localization of a Robot in a Real Home
topic Robotics
Deep learning
Semantic localization
CNN training
Neural networks
Robotics
Deep learning
Semantic localization
CNN training
Neural networks
url https://link.springer.com/chapter/10.1007/978-3-319-99885-5_1
https://ridda2.utp.ac.pa/handle/123456789/9446