Evolution of hybrid robotic controllers for complex tasks
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/9347 |
Resumo: | We propose an approach to the synthesis of hierarchical control systems comprising both evolved and manually programmed control for autonomous robots. We recursively divide the goal task into sub-tasks until a solution can be evolved or until a solution can easily be programmed by hand. Hierarchical composition of behavior allows us to overcome the fundamental challenges that typically prevent evolutionary robotics from being applied to complex tasks: bootstrapping the evolutionary process, avoiding deception, and successfully transferring control evolved in simulation to real robotic hardware. We demonstrate the proposed approach by synthesizing control systems for two tasks whose complexity is beyond state of the art in evolutionary robotics. The first task is a rescue task in which all behaviors are evolved. The second task is a cleaning task in which evolved behaviors are combined with a manually programmed behavior that enables the robot to open doors in the environment. We demonstrate incremental transfer of evolved control from simulation to real robotic hardware, and we show how our approach allows for the reuse of behaviors in different tasks. |
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Evolution of hybrid robotic controllers for complex tasksEvolutionary roboticsHierarchical controlArtificial evolutionWe propose an approach to the synthesis of hierarchical control systems comprising both evolved and manually programmed control for autonomous robots. We recursively divide the goal task into sub-tasks until a solution can be evolved or until a solution can easily be programmed by hand. Hierarchical composition of behavior allows us to overcome the fundamental challenges that typically prevent evolutionary robotics from being applied to complex tasks: bootstrapping the evolutionary process, avoiding deception, and successfully transferring control evolved in simulation to real robotic hardware. We demonstrate the proposed approach by synthesizing control systems for two tasks whose complexity is beyond state of the art in evolutionary robotics. The first task is a rescue task in which all behaviors are evolved. The second task is a cleaning task in which evolved behaviors are combined with a manually programmed behavior that enables the robot to open doors in the environment. We demonstrate incremental transfer of evolved control from simulation to real robotic hardware, and we show how our approach allows for the reuse of behaviors in different tasks.Springer2015-07-17T18:02:53Z2015-01-01T00:00:00Z20152019-03-26T17:23:38Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/9347eng0921-029610.1007/s10846-014-0086-xDuarte, M.Oliveira, S. M.Christensen, A. L.info: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:RCAAP2023-11-09T17:53:54Zoai:repositorio.iscte-iul.pt:10071/9347Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:27:05.122033Repositório 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 |
Evolution of hybrid robotic controllers for complex tasks |
title |
Evolution of hybrid robotic controllers for complex tasks |
spellingShingle |
Evolution of hybrid robotic controllers for complex tasks Duarte, M. Evolutionary robotics Hierarchical control Artificial evolution |
title_short |
Evolution of hybrid robotic controllers for complex tasks |
title_full |
Evolution of hybrid robotic controllers for complex tasks |
title_fullStr |
Evolution of hybrid robotic controllers for complex tasks |
title_full_unstemmed |
Evolution of hybrid robotic controllers for complex tasks |
title_sort |
Evolution of hybrid robotic controllers for complex tasks |
author |
Duarte, M. |
author_facet |
Duarte, M. Oliveira, S. M. Christensen, A. L. |
author_role |
author |
author2 |
Oliveira, S. M. Christensen, A. L. |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Duarte, M. Oliveira, S. M. Christensen, A. L. |
dc.subject.por.fl_str_mv |
Evolutionary robotics Hierarchical control Artificial evolution |
topic |
Evolutionary robotics Hierarchical control Artificial evolution |
description |
We propose an approach to the synthesis of hierarchical control systems comprising both evolved and manually programmed control for autonomous robots. We recursively divide the goal task into sub-tasks until a solution can be evolved or until a solution can easily be programmed by hand. Hierarchical composition of behavior allows us to overcome the fundamental challenges that typically prevent evolutionary robotics from being applied to complex tasks: bootstrapping the evolutionary process, avoiding deception, and successfully transferring control evolved in simulation to real robotic hardware. We demonstrate the proposed approach by synthesizing control systems for two tasks whose complexity is beyond state of the art in evolutionary robotics. The first task is a rescue task in which all behaviors are evolved. The second task is a cleaning task in which evolved behaviors are combined with a manually programmed behavior that enables the robot to open doors in the environment. We demonstrate incremental transfer of evolved control from simulation to real robotic hardware, and we show how our approach allows for the reuse of behaviors in different tasks. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-07-17T18:02:53Z 2015-01-01T00:00:00Z 2015 2019-03-26T17:23:38Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10071/9347 |
url |
http://hdl.handle.net/10071/9347 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0921-0296 10.1007/s10846-014-0086-x |
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 |
Springer |
publisher.none.fl_str_mv |
Springer |
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) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799134833718329344 |