Local models for inverse kinematics approximation of redundant robots: a performance comparison
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Biblioteca Digital de Teses e Dissertações da UFC |
Texto Completo: | http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=16727 |
Resumo: | In this dissertation it is reported the results of a comprehensive comparative study involving six local models applied to the task of learning the inverse kinematics of three redundant robotic arm (planar, PUMA 560 and Motoman HP6). The evaluated algorithms are the following ones: radial basis functions network (RBFN), local model network (LMN), SOMbased local linear mapping (LLM), local linear mapping over k-winners (K-SOM), local weighted regression (LWR) and counter propagation (CP). Each algorithm is evaluated with respect to its accuracy in estimating the joint angles given the cartesian coordinates which comprise end-effector trajectories within the robot workspace. A comprehensive evaluation of the performances of the aforementioned algorithms is carried out based on correlation analysis of the residuals. Finally, hypothesis testing procedures are also executed in order to verifying if there are significant differences in performance among the best algorithms. |
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Biblioteca Digital de Teses e Dissertações da UFC |
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info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisLocal models for inverse kinematics approximation of redundant robots: a performance comparisonModelos locais para aproximaÃÃo da cinemÃtica inversa de robÃs redundantes: um estudo comparativo2015-12-04Guilherme de Alencar Barreto32841450368http://lattes.cnpq.br/8902002461422112Ajalmar RÃgo da Rocha Neto84543787315http://lattes.cnpq.br/4524723055652545OtacÃlio da Mota Almeida26310112368http://lattes.cnpq.br/1721353262824215 02485127301http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4616440E5Humberto Ãcaro Pinto FontineleUniversidade Federal do CearÃPrograma de PÃs-GraduaÃÃo em Engenharia de TeleinformÃticaUFCBRModelos lineares locais RobÃtica Redes neurais CinemÃtica inversa Mapas auto-organizÃveis Local linear models Inverse kinematics Self-organizing mapsROBOTIZACAOIn this dissertation it is reported the results of a comprehensive comparative study involving six local models applied to the task of learning the inverse kinematics of three redundant robotic arm (planar, PUMA 560 and Motoman HP6). The evaluated algorithms are the following ones: radial basis functions network (RBFN), local model network (LMN), SOMbased local linear mapping (LLM), local linear mapping over k-winners (K-SOM), local weighted regression (LWR) and counter propagation (CP). Each algorithm is evaluated with respect to its accuracy in estimating the joint angles given the cartesian coordinates which comprise end-effector trajectories within the robot workspace. A comprehensive evaluation of the performances of the aforementioned algorithms is carried out based on correlation analysis of the residuals. Finally, hypothesis testing procedures are also executed in order to verifying if there are significant differences in performance among the best algorithms.Nesta dissertaÃÃo sÃo reportados os resultados de um amplo estudo comparativo envolvendo seis modelos locais aplicados à tarefa de aproximaÃÃo do modelo cinemÃtico inverso de 3 robÃs manipuladores (planar, PUMA 560 e Motoman HP6). Os modelos avaliados sÃo os seguintes: rede de funÃÃes de base radial (RBFN), rede de modelos locais (LMN), mapeamento linear local baseado em SOM (LLM), mapeamento linear local usando K vencedores (KSOM), regressÃo local ponderada (LWR) e rede counterpropagation (CP). Estes algoritmos sÃo avaliados quanto à acurÃcia na estimaÃÃo dos Ãngulos das juntas dos robÃs manipuladores em experimentos envolvendo a geraÃÃo de vÃrios tipos de trajetÃrias no espaÃo de trabalho dos referidos robÃs. Uma avaliaÃÃo abrangente do desempenho de cada algoritmo à feita com base na anÃlise dos resÃduos e testes de hipÃteses sÃo realizados para verificar a semelhanÃa estatistica entre os desempenhos dos melhores algoritmos.nÃo hÃhttp://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=16727application/pdfinfo:eu-repo/semantics/openAccessporreponame:Biblioteca Digital de Teses e Dissertações da UFCinstname:Universidade Federal do Cearáinstacron:UFC2019-01-21T11:30:04Zmail@mail.com - |
dc.title.en.fl_str_mv |
Local models for inverse kinematics approximation of redundant robots: a performance comparison |
dc.title.alternative.pt.fl_str_mv |
Modelos locais para aproximaÃÃo da cinemÃtica inversa de robÃs redundantes: um estudo comparativo |
title |
Local models for inverse kinematics approximation of redundant robots: a performance comparison |
spellingShingle |
Local models for inverse kinematics approximation of redundant robots: a performance comparison Humberto Ãcaro Pinto Fontinele Modelos lineares locais RobÃtica Redes neurais CinemÃtica inversa Mapas auto-organizÃveis Local linear models Inverse kinematics Self-organizing maps ROBOTIZACAO |
title_short |
Local models for inverse kinematics approximation of redundant robots: a performance comparison |
title_full |
Local models for inverse kinematics approximation of redundant robots: a performance comparison |
title_fullStr |
Local models for inverse kinematics approximation of redundant robots: a performance comparison |
title_full_unstemmed |
Local models for inverse kinematics approximation of redundant robots: a performance comparison |
title_sort |
Local models for inverse kinematics approximation of redundant robots: a performance comparison |
author |
Humberto Ãcaro Pinto Fontinele |
author_facet |
Humberto Ãcaro Pinto Fontinele |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Guilherme de Alencar Barreto |
dc.contributor.advisor1ID.fl_str_mv |
32841450368 |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/8902002461422112 |
dc.contributor.referee1.fl_str_mv |
Ajalmar RÃgo da Rocha Neto |
dc.contributor.referee1ID.fl_str_mv |
84543787315 |
dc.contributor.referee1Lattes.fl_str_mv |
http://lattes.cnpq.br/4524723055652545 |
dc.contributor.referee2.fl_str_mv |
OtacÃlio da Mota Almeida |
dc.contributor.referee2ID.fl_str_mv |
26310112368 |
dc.contributor.referee2Lattes.fl_str_mv |
http://lattes.cnpq.br/1721353262824215 |
dc.contributor.authorID.fl_str_mv |
02485127301 |
dc.contributor.authorLattes.fl_str_mv |
http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4616440E5 |
dc.contributor.author.fl_str_mv |
Humberto Ãcaro Pinto Fontinele |
contributor_str_mv |
Guilherme de Alencar Barreto Ajalmar RÃgo da Rocha Neto OtacÃlio da Mota Almeida |
dc.subject.por.fl_str_mv |
Modelos lineares locais RobÃtica Redes neurais CinemÃtica inversa Mapas auto-organizÃveis |
topic |
Modelos lineares locais RobÃtica Redes neurais CinemÃtica inversa Mapas auto-organizÃveis Local linear models Inverse kinematics Self-organizing maps ROBOTIZACAO |
dc.subject.eng.fl_str_mv |
Local linear models Inverse kinematics Self-organizing maps |
dc.subject.cnpq.fl_str_mv |
ROBOTIZACAO |
dc.description.sponsorship.fl_txt_mv |
nÃo hà |
dc.description.abstract.por.fl_txt_mv |
In this dissertation it is reported the results of a comprehensive comparative study involving six local models applied to the task of learning the inverse kinematics of three redundant robotic arm (planar, PUMA 560 and Motoman HP6). The evaluated algorithms are the following ones: radial basis functions network (RBFN), local model network (LMN), SOMbased local linear mapping (LLM), local linear mapping over k-winners (K-SOM), local weighted regression (LWR) and counter propagation (CP). Each algorithm is evaluated with respect to its accuracy in estimating the joint angles given the cartesian coordinates which comprise end-effector trajectories within the robot workspace. A comprehensive evaluation of the performances of the aforementioned algorithms is carried out based on correlation analysis of the residuals. Finally, hypothesis testing procedures are also executed in order to verifying if there are significant differences in performance among the best algorithms. Nesta dissertaÃÃo sÃo reportados os resultados de um amplo estudo comparativo envolvendo seis modelos locais aplicados à tarefa de aproximaÃÃo do modelo cinemÃtico inverso de 3 robÃs manipuladores (planar, PUMA 560 e Motoman HP6). Os modelos avaliados sÃo os seguintes: rede de funÃÃes de base radial (RBFN), rede de modelos locais (LMN), mapeamento linear local baseado em SOM (LLM), mapeamento linear local usando K vencedores (KSOM), regressÃo local ponderada (LWR) e rede counterpropagation (CP). Estes algoritmos sÃo avaliados quanto à acurÃcia na estimaÃÃo dos Ãngulos das juntas dos robÃs manipuladores em experimentos envolvendo a geraÃÃo de vÃrios tipos de trajetÃrias no espaÃo de trabalho dos referidos robÃs. Uma avaliaÃÃo abrangente do desempenho de cada algoritmo à feita com base na anÃlise dos resÃduos e testes de hipÃteses sÃo realizados para verificar a semelhanÃa estatistica entre os desempenhos dos melhores algoritmos. |
description |
In this dissertation it is reported the results of a comprehensive comparative study involving six local models applied to the task of learning the inverse kinematics of three redundant robotic arm (planar, PUMA 560 and Motoman HP6). The evaluated algorithms are the following ones: radial basis functions network (RBFN), local model network (LMN), SOMbased local linear mapping (LLM), local linear mapping over k-winners (K-SOM), local weighted regression (LWR) and counter propagation (CP). Each algorithm is evaluated with respect to its accuracy in estimating the joint angles given the cartesian coordinates which comprise end-effector trajectories within the robot workspace. A comprehensive evaluation of the performances of the aforementioned algorithms is carried out based on correlation analysis of the residuals. Finally, hypothesis testing procedures are also executed in order to verifying if there are significant differences in performance among the best algorithms. |
publishDate |
2015 |
dc.date.issued.fl_str_mv |
2015-12-04 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
status_str |
publishedVersion |
format |
masterThesis |
dc.identifier.uri.fl_str_mv |
http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=16727 |
url |
http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=16727 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal do Cearà |
dc.publisher.program.fl_str_mv |
Programa de PÃs-GraduaÃÃo em Engenharia de TeleinformÃtica |
dc.publisher.initials.fl_str_mv |
UFC |
dc.publisher.country.fl_str_mv |
BR |
publisher.none.fl_str_mv |
Universidade Federal do Cearà |
dc.source.none.fl_str_mv |
reponame:Biblioteca Digital de Teses e Dissertações da UFC instname:Universidade Federal do Ceará instacron:UFC |
reponame_str |
Biblioteca Digital de Teses e Dissertações da UFC |
collection |
Biblioteca Digital de Teses e Dissertações da UFC |
instname_str |
Universidade Federal do Ceará |
instacron_str |
UFC |
institution |
UFC |
repository.name.fl_str_mv |
-
|
repository.mail.fl_str_mv |
mail@mail.com |
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1643295220447576064 |