Extracting stairs and doors as natural landmarks for mobile robot localization from clouds of 3D edge-points
| Ano de defesa: | 2020 |
|---|---|
| Autor(a) principal: | |
| Orientador(a): | |
| Banca de defesa: | |
| Tipo de documento: | Tese |
| Tipo de acesso: | Acesso aberto |
| Idioma: | por |
| Instituição de defesa: |
Universidade Federal do Rio Grande do Norte
Brasil UFRN PROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA ELÉTRICA E DE COMPUTAÇÃO |
| Programa de Pós-Graduação: |
Não Informado pela instituição
|
| Departamento: |
Não Informado pela instituição
|
| País: |
Não Informado pela instituição
|
| Palavras-chave em Português: | |
| Link de acesso: | https://repositorio.ufrn.br/handle/123456789/31930 |
Resumo: | Natural landmarks are the main features in the next step of the research in localization of mobile robot platforms. The identification and recognition of these landmarks are crucial to better localize a robot. To help solving this problem, this work proposes an approach for the identification and recognition of natural marks included in the environment using images from RGB-D sensors. In the identification step, a structural analysis of the natural landmarks that are present in the environment is performed. The extraction of edge points of these landmarks is done using the 3D point cloud obtained from the RGBD sensor. These edge points are smoothed through the Sl0 algorithm, which minimizes the standard deviation of the normals at each point. Then, the second step of the proposed algorithm begins, which is the proper recognition of the natural landmarks. This recognition step is done as a real-time algorithm that extracts the points referring to the filtered edges and determines to which structure they belong to in the current scenario: stairs or doors. Finally, the geometrical characteristics that are intrinsic to the doors and stairs are identified. The approach proposed here has been validated with real robot experiments. The performed tests verify the efficacy of our proposed approach. |
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Extracting stairs and doors as natural landmarks for mobile robot localization from clouds of 3D edge-pointsMarcos naturaisSensores RGB-DNuvem de ponta 3DLocalização de robôNatural landmarks are the main features in the next step of the research in localization of mobile robot platforms. The identification and recognition of these landmarks are crucial to better localize a robot. To help solving this problem, this work proposes an approach for the identification and recognition of natural marks included in the environment using images from RGB-D sensors. In the identification step, a structural analysis of the natural landmarks that are present in the environment is performed. The extraction of edge points of these landmarks is done using the 3D point cloud obtained from the RGBD sensor. These edge points are smoothed through the Sl0 algorithm, which minimizes the standard deviation of the normals at each point. Then, the second step of the proposed algorithm begins, which is the proper recognition of the natural landmarks. This recognition step is done as a real-time algorithm that extracts the points referring to the filtered edges and determines to which structure they belong to in the current scenario: stairs or doors. Finally, the geometrical characteristics that are intrinsic to the doors and stairs are identified. The approach proposed here has been validated with real robot experiments. The performed tests verify the efficacy of our proposed approach.Marcas naturais são as principais características na próxima etapa da pesquisa em localização de plataformas de robôs móveis. A identificação e o reconhecimento de marcas são cruciais para melhor localizar um robô. Para ajudar a resolver este problema, este trabalho propõe uma abordagem para a identificação e reconhecimento de marcas naturais incluídas no ambiente utilizando imagens de sensores RGB-D. Na etapa de identificação, é realizada uma análise estrutural dos marcos naturais que estão presentes no ambiente. A extração dos pontos de borda desses marcos é feita usando a nuvem de pontos 3D obtida do sensor RGB-D. Esses pontos de borda são suavizados por meio do algoritmo Sl0, que minimiza o desvio padrão das normais em cada ponto. Então, começa a segunda etapa do algoritmo proposto, que é o reconhecimento adequado dos marcos naturais. Esta etapa de reconhecimento é feita como um algoritmo em tempo real que extrai os pontos referentes às arestas filtradas e determina a qual estrutura pertencem no cenário atual: escadas ou portas. Por fim, são identificadas as características geométricas intrínsecas às portas e escadas. A abordagem proposta aqui foi validada com experimentos reais de robôs. Os testes realizados verificam a eficácia de nossa abordagem proposta.Universidade Federal do Rio Grande do NorteBrasilUFRNPROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA ELÉTRICA E DE COMPUTAÇÃOGonçalves, Luiz Marcos Garciahttp://lattes.cnpq.br/7947681999420065http://lattes.cnpq.br/1562357566810393Nascimento, Tiago Pereira dohttp://lattes.cnpq.br/1641673656667170Gomes, Rafael Beserrahttp://lattes.cnpq.br/5849107545126304Silva, Bruno Marques Ferreira dahttp://lattes.cnpq.br/7878437620254155Souza, Anderson Abner de Santanahttp://lattes.cnpq.br/2563070123322776Souto, Leonardo Ângelo Virginio de2021-03-17T23:13:12Z2021-03-17T23:13:12Z2020-11-30info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfSOUTO, Leonardo Ângelo Virginio de. Extracting stairs and doors as natural landmarks for mobile robot localization from clouds of 3D edge-points. 2020. 64f. Tese (Doutorado em Engenharia Elétrica e de Computação) - Centro de Tecnologia, Universidade Federal do Rio Grande do Norte, Natal, 2020.https://repositorio.ufrn.br/handle/123456789/31930info:eu-repo/semantics/openAccessporreponame:Repositório Institucional da UFRNinstname:Universidade Federal do Rio Grande do Norte (UFRN)instacron:UFRN2021-03-21T08:48:16Zoai:repositorio.ufrn.br:123456789/31930Repositório InstitucionalPUBhttp://repositorio.ufrn.br/oai/repositorio@bczm.ufrn.bropendoar:2021-03-21T08:48:16Repositório Institucional da UFRN - Universidade Federal do Rio Grande do Norte (UFRN)false |
| dc.title.none.fl_str_mv |
Extracting stairs and doors as natural landmarks for mobile robot localization from clouds of 3D edge-points |
| title |
Extracting stairs and doors as natural landmarks for mobile robot localization from clouds of 3D edge-points |
| spellingShingle |
Extracting stairs and doors as natural landmarks for mobile robot localization from clouds of 3D edge-points Souto, Leonardo Ângelo Virginio de Marcos naturais Sensores RGB-D Nuvem de ponta 3D Localização de robô |
| title_short |
Extracting stairs and doors as natural landmarks for mobile robot localization from clouds of 3D edge-points |
| title_full |
Extracting stairs and doors as natural landmarks for mobile robot localization from clouds of 3D edge-points |
| title_fullStr |
Extracting stairs and doors as natural landmarks for mobile robot localization from clouds of 3D edge-points |
| title_full_unstemmed |
Extracting stairs and doors as natural landmarks for mobile robot localization from clouds of 3D edge-points |
| title_sort |
Extracting stairs and doors as natural landmarks for mobile robot localization from clouds of 3D edge-points |
| author |
Souto, Leonardo Ângelo Virginio de |
| author_facet |
Souto, Leonardo Ângelo Virginio de |
| author_role |
author |
| dc.contributor.none.fl_str_mv |
Gonçalves, Luiz Marcos Garcia http://lattes.cnpq.br/7947681999420065 http://lattes.cnpq.br/1562357566810393 Nascimento, Tiago Pereira do http://lattes.cnpq.br/1641673656667170 Gomes, Rafael Beserra http://lattes.cnpq.br/5849107545126304 Silva, Bruno Marques Ferreira da http://lattes.cnpq.br/7878437620254155 Souza, Anderson Abner de Santana http://lattes.cnpq.br/2563070123322776 |
| dc.contributor.author.fl_str_mv |
Souto, Leonardo Ângelo Virginio de |
| dc.subject.por.fl_str_mv |
Marcos naturais Sensores RGB-D Nuvem de ponta 3D Localização de robô |
| topic |
Marcos naturais Sensores RGB-D Nuvem de ponta 3D Localização de robô |
| description |
Natural landmarks are the main features in the next step of the research in localization of mobile robot platforms. The identification and recognition of these landmarks are crucial to better localize a robot. To help solving this problem, this work proposes an approach for the identification and recognition of natural marks included in the environment using images from RGB-D sensors. In the identification step, a structural analysis of the natural landmarks that are present in the environment is performed. The extraction of edge points of these landmarks is done using the 3D point cloud obtained from the RGBD sensor. These edge points are smoothed through the Sl0 algorithm, which minimizes the standard deviation of the normals at each point. Then, the second step of the proposed algorithm begins, which is the proper recognition of the natural landmarks. This recognition step is done as a real-time algorithm that extracts the points referring to the filtered edges and determines to which structure they belong to in the current scenario: stairs or doors. Finally, the geometrical characteristics that are intrinsic to the doors and stairs are identified. The approach proposed here has been validated with real robot experiments. The performed tests verify the efficacy of our proposed approach. |
| publishDate |
2020 |
| dc.date.none.fl_str_mv |
2020-11-30 2021-03-17T23:13:12Z 2021-03-17T23:13:12Z |
| dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
| dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
| format |
doctoralThesis |
| status_str |
publishedVersion |
| dc.identifier.uri.fl_str_mv |
SOUTO, Leonardo Ângelo Virginio de. Extracting stairs and doors as natural landmarks for mobile robot localization from clouds of 3D edge-points. 2020. 64f. Tese (Doutorado em Engenharia Elétrica e de Computação) - Centro de Tecnologia, Universidade Federal do Rio Grande do Norte, Natal, 2020. https://repositorio.ufrn.br/handle/123456789/31930 |
| identifier_str_mv |
SOUTO, Leonardo Ângelo Virginio de. Extracting stairs and doors as natural landmarks for mobile robot localization from clouds of 3D edge-points. 2020. 64f. Tese (Doutorado em Engenharia Elétrica e de Computação) - Centro de Tecnologia, Universidade Federal do Rio Grande do Norte, Natal, 2020. |
| url |
https://repositorio.ufrn.br/handle/123456789/31930 |
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por |
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por |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
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Universidade Federal do Rio Grande do Norte Brasil UFRN PROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA ELÉTRICA E DE COMPUTAÇÃO |
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Universidade Federal do Rio Grande do Norte Brasil UFRN PROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA ELÉTRICA E DE COMPUTAÇÃO |
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