Finding the Place: How to Train and Use Convolutional Neural Networks for a Dynamically Learning Robot
For a robot, the ability to adapt his knowledge automatically and customize its behavior is a key feature. Furthermore, a robot should be able to carry out its tasks at a long-term basis, performing it seamlessly in presence of changes in their surroundings. To do that, it is essential that the robo...
Bewaard in:
| Hoofdauteur: | |
|---|---|
| Andere auteurs: | , , , , |
| Formaat: | article |
| Taal: | Engels |
| Gepubliceerd in: |
2019
|
| Onderwerpen: | |
| Online toegang: | https://ieeexplore.ieee.org/abstract/document/8489469/keywords#keywords https://ridda2.utp.ac.pa/handle/123456789/9438 |
| Tags: |
Geen labels, Wees de eerste die dit record labelt!
|
| _version_ | 1869652460794019840 |
|---|---|
| author | Cruz, Edmanuel |
| author2 | Rangel, José Carlos Gomez Donoso, Francisco Bauer, Zuria Cazorla, Miguel García Rodríguez, José |
| author2_role | author author author author author |
| author_browse | Bauer, Zuria Cazorla, Miguel Cruz, Edmanuel García Rodríguez, José Gomez Donoso, Francisco Rangel, José Carlos |
| author_facet | Cruz, Edmanuel Rangel, José Carlos Gomez Donoso, Francisco Bauer, Zuria Cazorla, Miguel García Rodríguez, José |
| author_role | author |
| collection | Repositorio Institucional de documento digitales de acceso abierto de la UTP |
| dc.creator.none.fl_str_mv | Cruz, Edmanuel Rangel, José Carlos Gomez Donoso, Francisco Bauer, Zuria Cazorla, Miguel García Rodríguez, José |
| dc.date.none.fl_str_mv | 10/15/2018 10/15/2018 2019-12-17T20:50:46Z 2019-12-17T20:50:46Z 2019-12-17T20:50:46Z 2019-12-17T20:50:46Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | https://ieeexplore.ieee.org/abstract/document/8489469/keywords#keywords 2161-4407 https://ridda2.utp.ac.pa/handle/123456789/9438 https://ridda2.utp.ac.pa/handle/123456789/9438 |
| dc.language.none.fl_str_mv | eng en |
| 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 | Robots Semantics Training Feature extraction Computer architecture Task analysis Visualization Robots Semantics Training Feature extraction Computer architecture Task analysis Visualization |
| dc.title.none.fl_str_mv | Finding the Place: How to Train and Use Convolutional Neural Networks for a Dynamically Learning Robot |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| description | For a robot, the ability to adapt his knowledge automatically and customize its behavior is a key feature. Furthermore, a robot should be able to carry out its tasks at a long-term basis, performing it seamlessly in presence of changes in their surroundings. To do that, it is essential that the robot dynamically learn from their environment, but to perform a fully retraining of a deep learning architecture when the model needs new knowledge is a highly time consuming task. This work focus on exploring several strategies to include new data to an already learned model, applied to the semantic localization problem focusing in the accuracy of the final model and their training time. Exhaustive experimentation is carried out and each result is discussed consequently. |
| eu_rights_str_mv | embargoedAccess |
| format | article |
| id | lrtest_3e91ba28f31c51ccda5de614f200a05b |
| identifier_str_mv | 2161-4407 |
| instacron_str | U Tecnológica de Panamá |
| institution | U Tecnológica de Panamá |
| instname_str | Universidad Tecnológica de Panamá |
| language | eng |
| language_invalid_str_mv | en |
| network_acronym_str | lrtest |
| network_name_str | lr |
| oai_identifier_str | oai:ridda2.utp.ac.pa:123456789/9438 |
| publishDate | 2019 |
| publishDateSort | 2019 |
| reponame_str | Repositorio Institucional de documento digitales de acceso abierto de la UTP |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Finding the Place: How to Train and Use Convolutional Neural Networks for a Dynamically Learning RobotCruz, EdmanuelRangel, José CarlosGomez Donoso, FranciscoBauer, ZuriaCazorla, MiguelGarcía Rodríguez, JoséRobotsSemanticsTrainingFeature extractionComputer architectureTask analysisVisualizationRobotsSemanticsTrainingFeature extractionComputer architectureTask analysisVisualizationFor a robot, the ability to adapt his knowledge automatically and customize its behavior is a key feature. Furthermore, a robot should be able to carry out its tasks at a long-term basis, performing it seamlessly in presence of changes in their surroundings. To do that, it is essential that the robot dynamically learn from their environment, but to perform a fully retraining of a deep learning architecture when the model needs new knowledge is a highly time consuming task. This work focus on exploring several strategies to include new data to an already learned model, applied to the semantic localization problem focusing in the accuracy of the final model and their training time. Exhaustive experimentation is carried out and each result is discussed consequently.For a robot, the ability to adapt his knowledge automatically and customize its behavior is a key feature. Furthermore, a robot should be able to carry out its tasks at a long-term basis, performing it seamlessly in presence of changes in their surroundings. To do that, it is essential that the robot dynamically learn from their environment, but to perform a fully retraining of a deep learning architecture when the model needs new knowledge is a highly time consuming task. This work focus on exploring several strategies to include new data to an already learned model, applied to the semantic localization problem focusing in the accuracy of the final model and their training time. Exhaustive experimentation is carried out and each result is discussed consequently.2019-12-17T20:50:46Z2019-12-17T20:50:46Z2019-12-17T20:50:46Z2019-12-17T20:50:46Z10/15/201810/15/2018info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://ieeexplore.ieee.org/abstract/document/8489469/keywords#keywords2161-4407https://ridda2.utp.ac.pa/handle/123456789/9438https://ridda2.utp.ac.pa/handle/123456789/9438engeninfo: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:123456789/94382021-07-06T15:35:11Z |
| spellingShingle | Finding the Place: How to Train and Use Convolutional Neural Networks for a Dynamically Learning Robot Cruz, Edmanuel Robots Semantics Training Feature extraction Computer architecture Task analysis Visualization Robots Semantics Training Feature extraction Computer architecture Task analysis Visualization |
| status_str | publishedVersion |
| title | Finding the Place: How to Train and Use Convolutional Neural Networks for a Dynamically Learning Robot |
| title_full | Finding the Place: How to Train and Use Convolutional Neural Networks for a Dynamically Learning Robot |
| title_fullStr | Finding the Place: How to Train and Use Convolutional Neural Networks for a Dynamically Learning Robot |
| title_full_unstemmed | Finding the Place: How to Train and Use Convolutional Neural Networks for a Dynamically Learning Robot |
| title_short | Finding the Place: How to Train and Use Convolutional Neural Networks for a Dynamically Learning Robot |
| title_sort | Finding the Place: How to Train and Use Convolutional Neural Networks for a Dynamically Learning Robot |
| topic | Robots Semantics Training Feature extraction Computer architecture Task analysis Visualization Robots Semantics Training Feature extraction Computer architecture Task analysis Visualization |
| url | https://ieeexplore.ieee.org/abstract/document/8489469/keywords#keywords https://ridda2.utp.ac.pa/handle/123456789/9438 |