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dc.contributor.authorOsa Arzuaga, Nagore
dc.contributor.authorLasa, Ganix
dc.contributor.authorMazmela Etxabe, Maitane
dc.contributor.authorApraiz, Ainhoa
dc.contributor.authorEscallada Lopez, Oscar
dc.date.accessioned2026-01-21T08:15:02Z
dc.date.available2026-01-21T08:15:02Z
dc.date.issued2025
dc.identifier.issn1611-3349en
dc.identifier.otherhttps://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=200640en
dc.identifier.urihttps://hdl.handle.net/20.500.11984/14018
dc.description.abstractRobotic systems have progressed from isolated, pre-programmed manipulators to adaptive, learning agents capable of close collaboration with humans. This evolution outpaces most established Human–Robot Interaction (HRI) taxonomies and leaves design teams without a concise, human-centered method for specifying next-generation interactions. We present the Interaction Blueprint, a diagrammatic framework that merges service-design blueprinting with refined HRI concepts. Each task step is plotted on dual physical and cognitive axes and annotated across five layers—Activity, Role, Ability, Autonomy, and Authority-thereby linking user skills and decision prerogatives to robotic capabilities at the earliest design stage. The blueprint translates abstract taxonomic insights into a practical canvas for multidisciplinary teams and offers a scalable foundation for forthcoming empirical validation and metric integration.en
dc.language.isoengen
dc.publisherSpringer Natureen
dc.rights© 2025 Springer Natureen
dc.subjectODS 8 Trabajo decente y crecimiento económicoes
dc.subjectODS 9 Industria, innovación e infraestructuraes
dc.titleThe Interaction Blueprint: A Human-Centred Design Tool for Cognitive Human–Robot Interactionen
dcterms.accessRightshttp://purl.org/coar/access_right/c_f1cfen
dcterms.sourceInternational Conference on Social Roboticsen
local.contributor.groupCentro de Innovación en Diseñoes
local.description.peerreviewedtrueen
local.description.publicationfirstpage531en
local.description.publicationlastpage537en
local.identifier.doihttp://doi.org/10.1007/978-981-95-2382-5_38en
local.embargo.enddate2027-01-31
local.contributor.otherinstitutionhttps://ror.org/00wvqgd19es
local.source.details17 : 2025 : Napoles, 10-12 septiembre, 2025en
oaire.format.mimetypeapplication/pdfen
oaire.file$DSPACE\assetstoreen
oaire.resourceTypehttp://purl.org/coar/resource_type/c_c94fen
oaire.versionhttp://purl.org/coar/version/c_ab4af688f83e57aaen
dc.unesco.tesaurohttp://vocabularies.unesco.org/thesaurus/concept6459en
oaire.funderNameComisión Europeaen
oaire.funderIdentifierhttps://ror.org/00k4n6c32 / http://data.crossref.org/fundingdata/funder/10.13039/501100000780en
oaire.fundingStreamHorizon-RIAen
oaire.awardNumber101136067en
oaire.awardTitleINteractive robots that intuitiVely lEarn to inVErt tasks by ReaSoning about their Execution (INVERSE)en
oaire.awardURIhttps://doi.org/10.3030/101136067en
dc.unesco.clasificacionhttp://skos.um.es/unesco6/331003en


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