Co-evolution of morphology and controller for a robot
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/17826 |
Resumo: | Genetic algorithms are inspired by the process of natural selection that exists in nature. This process is what leads species to evolve and adapt to their surroundings, with the fittest species reproducing, leading to new generations that can take advantage of their surroundings better than before. This type of process can be used in evolutionary robotics to achieve controllers that are able to solve specific tasks to evolve morphologies for a specific purpose such as to walk, swim, grasp objects, among others. Robotic grippers are used in most factories nowadays, as well as in other workplaces such as hospitals and laboratories. They are used in tasks such as grabbing/moving objects, painting, surgeries, among many other uses. Grippers are therefore a case study with several possibilities that lend themselves to evolving morphologies through genetic algorithms. In this dissertation, we explore morphology generation through genetic algorithms. Using grippers as our case study, we were able to generate grippers capable of grabbing and lifting an object. To evolve these grippers, we created a simulated environment where grippers followed a script with instructions to grab the object and then move up. In total 120 different grippers were generated in these experiments. Out of those 120 generated grippers, 28% were able to grab and lift an object successfully. After the evaluation process was completed, we experimented with the grippers in five different scenarios to test their robustness. In these scenarios, the object’s starting conditions were different from those in the evaluation process. |
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Co-evolution of morphology and controller for a robotGripperMorphology generationGenetic algorithmsEngenharia eletrónicaAlgoritmo genéticoGeraçãoMorfologiaRobóticaAnálise de objetosGenetic algorithms are inspired by the process of natural selection that exists in nature. This process is what leads species to evolve and adapt to their surroundings, with the fittest species reproducing, leading to new generations that can take advantage of their surroundings better than before. This type of process can be used in evolutionary robotics to achieve controllers that are able to solve specific tasks to evolve morphologies for a specific purpose such as to walk, swim, grasp objects, among others. Robotic grippers are used in most factories nowadays, as well as in other workplaces such as hospitals and laboratories. They are used in tasks such as grabbing/moving objects, painting, surgeries, among many other uses. Grippers are therefore a case study with several possibilities that lend themselves to evolving morphologies through genetic algorithms. In this dissertation, we explore morphology generation through genetic algorithms. Using grippers as our case study, we were able to generate grippers capable of grabbing and lifting an object. To evolve these grippers, we created a simulated environment where grippers followed a script with instructions to grab the object and then move up. In total 120 different grippers were generated in these experiments. Out of those 120 generated grippers, 28% were able to grab and lift an object successfully. After the evaluation process was completed, we experimented with the grippers in five different scenarios to test their robustness. In these scenarios, the object’s starting conditions were different from those in the evaluation process.Os algoritmos genéticos são inspirados pelo processo de seleção natural que existe na natureza. Este processo leva espécies a evoluir e adaptar-se ao meio ambiente envolvente, com as espécies mais aptas reproduzindo, levando a que novas gerações possam tirar um melhor proveito do ambiente que as rodeia. Este tipo de processo pode ser utilizado na robótica evolucionária para evoluir controladores capazes de resolver tarefas de forma a evoluir morfologias para uma finalidade específica, tais como andar, nadar, agarrar objetos, entre outros. Garras robóticas são utilizadas na maioria das fábricas, assim como noutros locais de trabalho tais como hospitais e laboratórios. Podem ser utilizadas em tarefas como agarrar/mover objetos, pintura, cirurgias, entre outros usos. São, portanto, um caso de estudo com várias possibilidades que se prestam à evolução de morfologias através de algoritmos genéticos. Nesta dissertação, exploramos a geração de morfologia através de algoritmos genéticos. Utilizando garras como o nosso caso de estudo, conseguimos gerar garras capazes de agarrar e levantar um objeto. Para evoluir essas garras, criamos um ambiente simulado onde cada garra seguiu um script com instruções para agarrar o objeto e, em seguida, mover para cima. No total, 120 garras diferentes foram geradas nestas experiências. Dessas garras geradas 120, 28% foram capazes de capturar e levantar um objeto com êxito. Após a conclusão do processo de avaliação, experimentamos as garras em cinco cenários diferentes para testar a sua robustez. Nesses cenários, as condições iniciais em que os objetos começam eram diferentes das do processo de avaliação.2019-04-15T09:21:03Z2018-11-20T00:00:00Z2018-11-202018-09info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfapplication/octet-streamhttp://hdl.handle.net/10071/17826TID:202127397engSilva, Ivo Manuel Caeiro dainfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-09T17:37:38Zoai:repositorio.iscte-iul.pt:10071/17826Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:17:10.533117Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Co-evolution of morphology and controller for a robot |
title |
Co-evolution of morphology and controller for a robot |
spellingShingle |
Co-evolution of morphology and controller for a robot Silva, Ivo Manuel Caeiro da Gripper Morphology generation Genetic algorithms Engenharia eletrónica Algoritmo genético Geração Morfologia Robótica Análise de objetos |
title_short |
Co-evolution of morphology and controller for a robot |
title_full |
Co-evolution of morphology and controller for a robot |
title_fullStr |
Co-evolution of morphology and controller for a robot |
title_full_unstemmed |
Co-evolution of morphology and controller for a robot |
title_sort |
Co-evolution of morphology and controller for a robot |
author |
Silva, Ivo Manuel Caeiro da |
author_facet |
Silva, Ivo Manuel Caeiro da |
author_role |
author |
dc.contributor.author.fl_str_mv |
Silva, Ivo Manuel Caeiro da |
dc.subject.por.fl_str_mv |
Gripper Morphology generation Genetic algorithms Engenharia eletrónica Algoritmo genético Geração Morfologia Robótica Análise de objetos |
topic |
Gripper Morphology generation Genetic algorithms Engenharia eletrónica Algoritmo genético Geração Morfologia Robótica Análise de objetos |
description |
Genetic algorithms are inspired by the process of natural selection that exists in nature. This process is what leads species to evolve and adapt to their surroundings, with the fittest species reproducing, leading to new generations that can take advantage of their surroundings better than before. This type of process can be used in evolutionary robotics to achieve controllers that are able to solve specific tasks to evolve morphologies for a specific purpose such as to walk, swim, grasp objects, among others. Robotic grippers are used in most factories nowadays, as well as in other workplaces such as hospitals and laboratories. They are used in tasks such as grabbing/moving objects, painting, surgeries, among many other uses. Grippers are therefore a case study with several possibilities that lend themselves to evolving morphologies through genetic algorithms. In this dissertation, we explore morphology generation through genetic algorithms. Using grippers as our case study, we were able to generate grippers capable of grabbing and lifting an object. To evolve these grippers, we created a simulated environment where grippers followed a script with instructions to grab the object and then move up. In total 120 different grippers were generated in these experiments. Out of those 120 generated grippers, 28% were able to grab and lift an object successfully. After the evaluation process was completed, we experimented with the grippers in five different scenarios to test their robustness. In these scenarios, the object’s starting conditions were different from those in the evaluation process. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-11-20T00:00:00Z 2018-11-20 2018-09 2019-04-15T09:21:03Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10071/17826 TID:202127397 |
url |
http://hdl.handle.net/10071/17826 |
identifier_str_mv |
TID:202127397 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf application/octet-stream |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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