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Title
The Interaction Blueprint: A Human-Centred Design Tool for Cognitive Human–Robot Interaction
Author
Osa Arzuaga, Nagore
Lasa, Ganix
Mazmela Etxabe, Maitane
Apraiz, Ainhoa
Escallada Lopez, Oscar
Research Group
Centro de Innovación en Diseño
Other institutions
https://ror.org/00wvqgd19
Version
Postprint
Document type
Conference Object
Embargo end date
2027-01-31
Language
English
Rights
© 2025 Springer Nature
Access
Embargoed access
URI
https://hdl.handle.net/20.500.11984/14018
Publisher’s version
http://doi.org/10.1007/978-981-95-2382-5_38
Published at
International Conference on Social Robotics  17 : 2025 : Napoles, 10-12 septiembre, 2025
Publisher
Springer Nature
Keywords
ODS 8 Trabajo decente y crecimiento económico
ODS 9 Industria, innovación e infraestructura
Subject (UNESCO Thesaurus)
Industrial design
Abstract
Robotic 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 ... [+]
Robotic 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. [-]
Funder
Comisión Europea
Program
Horizon-RIA
Number
101136067
Award URI
https://doi.org/10.3030/101136067
Project
INteractive robots that intuitiVely lEarn to inVErt tasks by ReaSoning about their Execution (INVERSE)
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  • Conference papers - Engineering [466]

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