dc.rights.license | Attribution 4.0 International | |
dc.contributor.author | Apraiz Iriarte, Ainhoa | |
dc.contributor.author | Lasa, Ganix | |
dc.contributor.author | Mazmela Etxabe, Maitane | |
dc.contributor.author | Nguyen Ngoc, Hien | |
dc.contributor.other | Mulet Alberola, Jose A. | |
dc.date.accessioned | 2024-02-02T08:53:17Z | |
dc.date.available | 2024-02-02T08:53:17Z | |
dc.date.issued | 2023 | |
dc.identifier.issn | 2296-9144 | |
dc.identifier.other | https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=173301 | |
dc.identifier.uri | https://hdl.handle.net/20.500.11984/6236 | |
dc.description.abstract | Humans and robots will increasingly have to work together in the new industrial context. Therefore, it is necessary to improve the User Experience, Technology Acceptance, and overall wellbeing to achieve a smoother and more satisfying interaction while obtaining the maximum performance possible out of it. For this reason, it is essential to analyze these interactions to enhance User Experience. The heuristic evaluation is an easy-to-use, low-cost method that can be applied at different stages of a design process in an iterative manner. Despite these advantages, there is rarely a list of heuristics in the current literature that evaluates Human-Robot interactions both from a User Experience, Technology Acceptance, and Human-Centered approach. Such an approach should integrate key aspects like safety, trust, and perceived safety, ergonomics and workload, inclusivity, and multimodality, as well as robot characteristics and functionalities. Therefore, a new set of heuristics, namely, the HEUROBOX tool, is presented in this work in the form of the HEUROBOX tool to help practitioners and researchers in the assessment of human-robot systems in industrial environments. The HEUROBOX tool clusters design guidelines and methodologies as a logic list of heuristics for human-robot interaction and comprises four categories: Safety, Ergonomics, Functionality, and Interfaces. They include 84 heuristics in the basic evaluation, while the advanced evaluation lists a total of 228 heuristics in order to adapt the tool to the evaluation of different industrial requirements. Finally, the set of new heuristics has been validated by experts using the System Usability Scale (SUS) questionnaire and the categories has been prioritized in order of their importance in the evaluation of Human-Robot Interaction through the Analytic Hierarchy Process (AHP). | en |
dc.language.iso | eng | |
dc.publisher | Frontiers | |
dc.rights | © 2023 The Authors | |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
dc.subject | human-robot collaboration (HRC) | |
dc.subject | human-robot interaction (HRI), | |
dc.subject | user experience (UX) | |
dc.subject | technology acceptance | |
dc.subject | ODS 9 Industria, innovación e infraestructura | |
dc.subject | heuristic evaluation | |
dc.subject | industry 5.0 | |
dc.subject | human-centered | |
dc.title | Development of a new set of Heuristics for the evaluation of Human-Robot Interaction in industrial settings: Heuristics Robots Experience (HEUROBOX) | |
dcterms.accessRights | http://purl.org/coar/access_right/c_abf2 | |
dcterms.source | Frontiers in Robotics and AI | |
local.contributor.group | Centro de Innovación en Diseño | |
local.description.peerreviewed | true | |
local.identifier.doi | https://doi.org/10.3389/frobt.2023.1227082 | |
local.rights.publicationfee | APC | |
local.rights.publicationfeeamount | 2080 USD | |
local.contributor.otherinstitution | https://ror.org/02q2d2610 | |
local.contributor.otherinstitution | Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing (STIIMA) | |
local.source.details | Vol. 10 | |
oaire.format.mimetype | application/pdf | |
oaire.file | $DSPACE\assetstore | |
oaire.resourceType | http://purl.org/coar/resource_type/c_6501 | |
oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |
oaire.funderName | European Commission | |
oaire.funderIdentifier | https://ror.org/00k4n6c32 http://data.crossref.org/fundingdata/funder/10.13039/501100000780 | |
oaire.fundingStream | H2020 | |
oaire.awardNumber | 814078 | |
oaire.awardTitle | Digital Manufacturing and Design Training Network (DiManD) | |
oaire.awardURI | https://doi.org/10.3030/814078 | |