Classification and characterization of places for mapping of environment using hierarchical neural network and omnivision
Autor(a) principal: | |
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Data de Publicação: | 2008 |
Outros Autores: | , , , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1109/IWSSIP.2008.4604472 http://hdl.handle.net/11449/21815 |
Resumo: | Mobile robots need autonomy to fulfill their tasks. Such autonomy is related whith their capacity to explorer and to recognize their navigation environments. In this context, the present work considers techniques for the classification and extraction of features from images, using artificial neural networks. This images are used in the mapping and localization system of LACE (Automation and Evolutive Computing Laboratory) mobile robot. In this direction, the robot uses a sensorial system composed by ultrasound sensors and a catadioptric vision system equipped with a camera and a conical mirror. The mapping system is composed of three modules; two of them will be presented in this paper: the classifier and the characterizer modules. Results of these modules simulations are presented in this paper. |
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Classification and characterization of places for mapping of environment using hierarchical neural network and omnivisionomnivisionmapping systemhierarchical artificial neural network (RNAH)attributes vectoraffine invariant patternMobile robots need autonomy to fulfill their tasks. Such autonomy is related whith their capacity to explorer and to recognize their navigation environments. In this context, the present work considers techniques for the classification and extraction of features from images, using artificial neural networks. This images are used in the mapping and localization system of LACE (Automation and Evolutive Computing Laboratory) mobile robot. In this direction, the robot uses a sensorial system composed by ultrasound sensors and a catadioptric vision system equipped with a camera and a conical mirror. The mapping system is composed of three modules; two of them will be presented in this paper: the classifier and the characterizer modules. Results of these modules simulations are presented in this paper.São Paulo State Univ UNESP, Automat & Evolut Comp Lab, Comp & Stat Sci Dept, BR-2265 Sao Jose do Rio Preto, SP, BrazilSão Paulo State Univ UNESP, Automat & Evolut Comp Lab, Comp & Stat Sci Dept, BR-2265 Sao Jose do Rio Preto, SP, BrazilSlovak Univ Tech BratislavaUniversidade Estadual Paulista (Unesp)Silva, Luciana L. [UNESP]Tronco, Mario L. [UNESP]Vian, Henrique A. [UNESP]Souza, Rogeria C. G. [UNESP]Porto, Arthur J. V.2014-05-20T14:01:49Z2014-05-20T14:01:49Z2008-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject487-490http://dx.doi.org/10.1109/IWSSIP.2008.4604472Proceedings of Iwssip 2008: 15th International Conference on Systems, Signals and Image Processing. Bratislava: Slovak Univ Tech Bratislava, p. 487-490, 2008.http://hdl.handle.net/11449/21815WOS:000259363700121Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengProceedings of Iwssip 2008: 15th International Conference on Systems, Signals and Image Processinginfo:eu-repo/semantics/openAccess2021-10-23T21:37:53Zoai:repositorio.unesp.br:11449/21815Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T20:36:44.676308Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Classification and characterization of places for mapping of environment using hierarchical neural network and omnivision |
title |
Classification and characterization of places for mapping of environment using hierarchical neural network and omnivision |
spellingShingle |
Classification and characterization of places for mapping of environment using hierarchical neural network and omnivision Silva, Luciana L. [UNESP] omnivision mapping system hierarchical artificial neural network (RNAH) attributes vector affine invariant pattern |
title_short |
Classification and characterization of places for mapping of environment using hierarchical neural network and omnivision |
title_full |
Classification and characterization of places for mapping of environment using hierarchical neural network and omnivision |
title_fullStr |
Classification and characterization of places for mapping of environment using hierarchical neural network and omnivision |
title_full_unstemmed |
Classification and characterization of places for mapping of environment using hierarchical neural network and omnivision |
title_sort |
Classification and characterization of places for mapping of environment using hierarchical neural network and omnivision |
author |
Silva, Luciana L. [UNESP] |
author_facet |
Silva, Luciana L. [UNESP] Tronco, Mario L. [UNESP] Vian, Henrique A. [UNESP] Souza, Rogeria C. G. [UNESP] Porto, Arthur J. V. |
author_role |
author |
author2 |
Tronco, Mario L. [UNESP] Vian, Henrique A. [UNESP] Souza, Rogeria C. G. [UNESP] Porto, Arthur J. V. |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Silva, Luciana L. [UNESP] Tronco, Mario L. [UNESP] Vian, Henrique A. [UNESP] Souza, Rogeria C. G. [UNESP] Porto, Arthur J. V. |
dc.subject.por.fl_str_mv |
omnivision mapping system hierarchical artificial neural network (RNAH) attributes vector affine invariant pattern |
topic |
omnivision mapping system hierarchical artificial neural network (RNAH) attributes vector affine invariant pattern |
description |
Mobile robots need autonomy to fulfill their tasks. Such autonomy is related whith their capacity to explorer and to recognize their navigation environments. In this context, the present work considers techniques for the classification and extraction of features from images, using artificial neural networks. This images are used in the mapping and localization system of LACE (Automation and Evolutive Computing Laboratory) mobile robot. In this direction, the robot uses a sensorial system composed by ultrasound sensors and a catadioptric vision system equipped with a camera and a conical mirror. The mapping system is composed of three modules; two of them will be presented in this paper: the classifier and the characterizer modules. Results of these modules simulations are presented in this paper. |
publishDate |
2008 |
dc.date.none.fl_str_mv |
2008-01-01 2014-05-20T14:01:49Z 2014-05-20T14:01:49Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1109/IWSSIP.2008.4604472 Proceedings of Iwssip 2008: 15th International Conference on Systems, Signals and Image Processing. Bratislava: Slovak Univ Tech Bratislava, p. 487-490, 2008. http://hdl.handle.net/11449/21815 WOS:000259363700121 |
url |
http://dx.doi.org/10.1109/IWSSIP.2008.4604472 http://hdl.handle.net/11449/21815 |
identifier_str_mv |
Proceedings of Iwssip 2008: 15th International Conference on Systems, Signals and Image Processing. Bratislava: Slovak Univ Tech Bratislava, p. 487-490, 2008. WOS:000259363700121 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Proceedings of Iwssip 2008: 15th International Conference on Systems, Signals and Image Processing |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
487-490 |
dc.publisher.none.fl_str_mv |
Slovak Univ Tech Bratislava |
publisher.none.fl_str_mv |
Slovak Univ Tech Bratislava |
dc.source.none.fl_str_mv |
Web of Science reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129226827628544 |