Adapting robot task planning to user preferences: an assistive shoe dressing example

Healthcare robots will be the next big advance in humans’ domestic welfare, with robots able to assist elderly people and users with disabilities. However, each user has his/her own preferences, needs and abilities. Therefore, robotic assistants will need to adapt to them, behaving accordingly. Towa...

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Detalles Bibliográficos
Autores: Canal, Gerard, Alenyà, Guillem, Torras, Carme
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2019
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/202017
Acceso en línea:http://hdl.handle.net/10261/202017
Access Level:acceso abierto
Palabra clave:Planning with preferences
Behavior adaptation
Task personalization
Shoe fitting
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spelling Adapting robot task planning to user preferences: an assistive shoe dressing exampleCanal, GerardAlenyà, GuillemTorras, CarmePlanning with preferencesBehavior adaptationTask personalizationShoe fittingHealthcare robots will be the next big advance in humans’ domestic welfare, with robots able to assist elderly people and users with disabilities. However, each user has his/her own preferences, needs and abilities. Therefore, robotic assistants will need to adapt to them, behaving accordingly. Towards this goal, we propose a method to perform behavior adaptation to the user preferences, using symbolic task planning. A user model is built from the user’s answers to simple questions with a fuzzy inference system, and it is then integrated into the planning domain. We describe an adaptation method based on both the user satisfaction and the execution outcome, depending on which penalizations are applied to the planner’s rules. We demonstrate the application of the adaptation method in a simple shoe-fitting scenario, with experiments performed in a simulated user environment. The results show quick behavior adaptation, even when the user behavior changes, as well as robustness to wrong inference of the initial user model. Finally, some insights in a non-simulated world shoe-fitting setup are also provided.This work has been partially supported by the CHIST-ERA Project I-DRESS PCIN-2015-147, by the Spanish Ministry of Science and Innovation HuMoUR TIN2017-90086-R and the AEI through the María de Maeztu Seal of Excellence to IRI (MDM-2016-0656). Gerard Canal is also supported by the Spanish Ministry of Education, Culture and Sport via a doctoral grant FPU15/00504.Springer NatureMinisterio de Economía y Competitividad (España)Agencia Estatal de Investigación (España)Ministerio de Ciencia, Innovación y Universidades (España)Ministerio de Educación, Cultura y Deporte (España)Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]2020202020192020info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Postprintinfo:eu-repo/semantics/acceptedVersionhttp://hdl.handle.net/10261/202017reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/PCIN-2015-147TIN2017-90086-R/AEI/10.13039/501100011033info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/TIN2017-90086-Rinfo:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MDM-2016-0656http://dx.doi.org/10.1007/s10514-018-9737-2Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/2020172026-05-22T06:33:51Z
dc.title.none.fl_str_mv Adapting robot task planning to user preferences: an assistive shoe dressing example
title Adapting robot task planning to user preferences: an assistive shoe dressing example
spellingShingle Adapting robot task planning to user preferences: an assistive shoe dressing example
Canal, Gerard
Planning with preferences
Behavior adaptation
Task personalization
Shoe fitting
title_short Adapting robot task planning to user preferences: an assistive shoe dressing example
title_full Adapting robot task planning to user preferences: an assistive shoe dressing example
title_fullStr Adapting robot task planning to user preferences: an assistive shoe dressing example
title_full_unstemmed Adapting robot task planning to user preferences: an assistive shoe dressing example
title_sort Adapting robot task planning to user preferences: an assistive shoe dressing example
dc.creator.none.fl_str_mv Canal, Gerard
Alenyà, Guillem
Torras, Carme
author Canal, Gerard
author_facet Canal, Gerard
Alenyà, Guillem
Torras, Carme
author_role author
author2 Alenyà, Guillem
Torras, Carme
author2_role author
author
dc.contributor.none.fl_str_mv Ministerio de Economía y Competitividad (España)
Agencia Estatal de Investigación (España)
Ministerio de Ciencia, Innovación y Universidades (España)
Ministerio de Educación, Cultura y Deporte (España)
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Planning with preferences
Behavior adaptation
Task personalization
Shoe fitting
topic Planning with preferences
Behavior adaptation
Task personalization
Shoe fitting
description Healthcare robots will be the next big advance in humans’ domestic welfare, with robots able to assist elderly people and users with disabilities. However, each user has his/her own preferences, needs and abilities. Therefore, robotic assistants will need to adapt to them, behaving accordingly. Towards this goal, we propose a method to perform behavior adaptation to the user preferences, using symbolic task planning. A user model is built from the user’s answers to simple questions with a fuzzy inference system, and it is then integrated into the planning domain. We describe an adaptation method based on both the user satisfaction and the execution outcome, depending on which penalizations are applied to the planner’s rules. We demonstrate the application of the adaptation method in a simple shoe-fitting scenario, with experiments performed in a simulated user environment. The results show quick behavior adaptation, even when the user behavior changes, as well as robustness to wrong inference of the initial user model. Finally, some insights in a non-simulated world shoe-fitting setup are also provided.
publishDate 2019
dc.date.none.fl_str_mv 2019
2020
2020
2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Postprint
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/202017
url http://hdl.handle.net/10261/202017
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
#PLACEHOLDER_PARENT_METADATA_VALUE#
#PLACEHOLDER_PARENT_METADATA_VALUE#
#PLACEHOLDER_PARENT_METADATA_VALUE#
info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/PCIN-2015-147
TIN2017-90086-R/AEI/10.13039/501100011033
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/TIN2017-90086-R
info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MDM-2016-0656
http://dx.doi.org/10.1007/s10514-018-9737-2
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Springer Nature
publisher.none.fl_str_mv Springer Nature
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
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