Didactic use of genetic algorithms: a model for teaching robotics
Autor(a) principal: | |
---|---|
Data de Publicação: | 2020 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista Brasileira de Ensino de Ciência e Tecnologia |
Texto Completo: | https://periodicos.utfpr.edu.br/rbect/article/view/8218 |
Resumo: | The study of articulated robots in higher education necessarily goes through the development of their kinematic models. The inverse kinematic model is usually described algebraically, although this representation is often difficult to obtain. Thus, the use of genetic algorithms in teaching robotics can be very attractive, since they allow students to easily develop models and predict the behavior of robots before their formal development. This way, the results of this work present a relatively fast way to simulate the inverse kinematic model, allowing the designer to have a broader view of the structure of a robot, coming to identify points that must be corrected or that can be optimized. It can be concluded that the use of genetic algorithms in robotics teaching is viable, having as main advantages their easy computational implementation and precision in the representation of kinematic models.. |
id |
UTFPR-7_01fdcce154f9dc97b95fbf8e25c8915f |
---|---|
oai_identifier_str |
oai:periodicos.utfpr:article/8218 |
network_acronym_str |
UTFPR-7 |
network_name_str |
Revista Brasileira de Ensino de Ciência e Tecnologia |
repository_id_str |
|
spelling |
Didactic use of genetic algorithms: a model for teaching roboticsCiência da computação; matemática da computação; modelos analíticos e de simulaçãoEvolutionary algorithms; Process optimization; Computer simulationThe study of articulated robots in higher education necessarily goes through the development of their kinematic models. The inverse kinematic model is usually described algebraically, although this representation is often difficult to obtain. Thus, the use of genetic algorithms in teaching robotics can be very attractive, since they allow students to easily develop models and predict the behavior of robots before their formal development. This way, the results of this work present a relatively fast way to simulate the inverse kinematic model, allowing the designer to have a broader view of the structure of a robot, coming to identify points that must be corrected or that can be optimized. It can be concluded that the use of genetic algorithms in robotics teaching is viable, having as main advantages their easy computational implementation and precision in the representation of kinematic models..Universidade Tecnológica Federal do Paraná (UTFPR)Franco de Camargo, José TarcísioAnunciato Franco de Camargo, ElianaVizconde Veraszto, EstéfanoBarreto, GilmarCândido, Jorge2020-04-15info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.utfpr.edu.br/rbect/article/view/821810.3895/rbect.v13n1.8218Revista Brasileira de Ensino de Ciência e Tecnologia; v. 13, n. 1 (2020)1982-873X10.3895/rbect.v13n1reponame:Revista Brasileira de Ensino de Ciência e Tecnologiainstname:Universidade Tecnológica Federal do Paraná (UTFPR)instacron:UTFPRenghttps://periodicos.utfpr.edu.br/rbect/article/view/8218/pdfDireitos autorais 2020 CC-BYhttp://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccess2022-09-29T18:40:50Zoai:periodicos.utfpr:article/8218Revistahttps://periodicos.utfpr.edu.br/rbectPUBhttps://periodicos.utfpr.edu.br/rbect/oai||rbect-pg@utfpr.edu.br1982-873X1982-873Xopendoar:2022-09-29T18:40:50Revista Brasileira de Ensino de Ciência e Tecnologia - Universidade Tecnológica Federal do Paraná (UTFPR)false |
dc.title.none.fl_str_mv |
Didactic use of genetic algorithms: a model for teaching robotics |
title |
Didactic use of genetic algorithms: a model for teaching robotics |
spellingShingle |
Didactic use of genetic algorithms: a model for teaching robotics Franco de Camargo, José Tarcísio Ciência da computação; matemática da computação; modelos analíticos e de simulação Evolutionary algorithms; Process optimization; Computer simulation |
title_short |
Didactic use of genetic algorithms: a model for teaching robotics |
title_full |
Didactic use of genetic algorithms: a model for teaching robotics |
title_fullStr |
Didactic use of genetic algorithms: a model for teaching robotics |
title_full_unstemmed |
Didactic use of genetic algorithms: a model for teaching robotics |
title_sort |
Didactic use of genetic algorithms: a model for teaching robotics |
author |
Franco de Camargo, José Tarcísio |
author_facet |
Franco de Camargo, José Tarcísio Anunciato Franco de Camargo, Eliana Vizconde Veraszto, Estéfano Barreto, Gilmar Cândido, Jorge |
author_role |
author |
author2 |
Anunciato Franco de Camargo, Eliana Vizconde Veraszto, Estéfano Barreto, Gilmar Cândido, Jorge |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
|
dc.contributor.author.fl_str_mv |
Franco de Camargo, José Tarcísio Anunciato Franco de Camargo, Eliana Vizconde Veraszto, Estéfano Barreto, Gilmar Cândido, Jorge |
dc.subject.por.fl_str_mv |
Ciência da computação; matemática da computação; modelos analíticos e de simulação Evolutionary algorithms; Process optimization; Computer simulation |
topic |
Ciência da computação; matemática da computação; modelos analíticos e de simulação Evolutionary algorithms; Process optimization; Computer simulation |
description |
The study of articulated robots in higher education necessarily goes through the development of their kinematic models. The inverse kinematic model is usually described algebraically, although this representation is often difficult to obtain. Thus, the use of genetic algorithms in teaching robotics can be very attractive, since they allow students to easily develop models and predict the behavior of robots before their formal development. This way, the results of this work present a relatively fast way to simulate the inverse kinematic model, allowing the designer to have a broader view of the structure of a robot, coming to identify points that must be corrected or that can be optimized. It can be concluded that the use of genetic algorithms in robotics teaching is viable, having as main advantages their easy computational implementation and precision in the representation of kinematic models.. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-04-15 |
dc.type.none.fl_str_mv |
|
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://periodicos.utfpr.edu.br/rbect/article/view/8218 10.3895/rbect.v13n1.8218 |
url |
https://periodicos.utfpr.edu.br/rbect/article/view/8218 |
identifier_str_mv |
10.3895/rbect.v13n1.8218 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://periodicos.utfpr.edu.br/rbect/article/view/8218/pdf |
dc.rights.driver.fl_str_mv |
Direitos autorais 2020 CC-BY http://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Direitos autorais 2020 CC-BY http://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Tecnológica Federal do Paraná (UTFPR) |
publisher.none.fl_str_mv |
Universidade Tecnológica Federal do Paraná (UTFPR) |
dc.source.none.fl_str_mv |
Revista Brasileira de Ensino de Ciência e Tecnologia; v. 13, n. 1 (2020) 1982-873X 10.3895/rbect.v13n1 reponame:Revista Brasileira de Ensino de Ciência e Tecnologia instname:Universidade Tecnológica Federal do Paraná (UTFPR) instacron:UTFPR |
instname_str |
Universidade Tecnológica Federal do Paraná (UTFPR) |
instacron_str |
UTFPR |
institution |
UTFPR |
reponame_str |
Revista Brasileira de Ensino de Ciência e Tecnologia |
collection |
Revista Brasileira de Ensino de Ciência e Tecnologia |
repository.name.fl_str_mv |
Revista Brasileira de Ensino de Ciência e Tecnologia - Universidade Tecnológica Federal do Paraná (UTFPR) |
repository.mail.fl_str_mv |
||rbect-pg@utfpr.edu.br |
_version_ |
1787713871922855936 |