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dc.contributor.authorLlop-Harillo, Immaculada
dc.contributor.authorIserte, José Luis
dc.contributor.authorPérez-González, Antonio
dc.date.accessioned2022-03-09T12:07:54Z
dc.date.available2022-03-09T12:07:54Z
dc.date.issued2022-02-25
dc.identifier.citationImmaculada Llop-Harillo, José L Iserte, Antonio Pérez-González, Benchmarking anthropomorphic hands through grasping simulations, Journal of Computational Design and Engineering, Volume 9, Issue 2, April 2022, Pages 330–342, https://doi.org/10.1093/jcde/qwac002ca_CA
dc.identifier.issn2288-5048
dc.identifier.urihttp://hdl.handle.net/10234/196976
dc.description.abstractIn recent decades, the design of anthropomorphic hands has been developed greatly improving both cosmesis and functionality. Experimentation, simulation, and combined approaches have been used in the literature to assess the effect of design alternatives (DAs) on the final performance of artificial hands. However, establishing standard benchmarks for grasping and manipulation is a need recognized among the robotics community. Experimental approaches are costly, time consuming, and inconvenient in early design stages. Alternatively, computer simulation with the adaptation of metrics based on experimental benchmarks for anthropomorphic hands could be useful to evaluate and rank DAs. The aim of this study is to compare the anthropomorphism of the grasps performed with 28 DAs of the IMMA hand, developed by the authors, using either (i) the brute-force approach and grasp quality metrics proposed in previous works or (ii) a new simulation benchmark approach. The new methodology involves the generation of efficient grasp hypotheses and the definition of a new metric to assess stability and human likeness for the most frequently used grasp types in activities of daily living, pulp pinch and cylindrical grip, adapting the experimental Anthropomorphic Hand Assessment Protocol to the simulation environment. This new simulation benchmark, in contrast to the other approach, resulted in anthropomorphic and more realistic grasps for the expected use of the objects. Despite the inherent limitations of a simulation analysis, the benchmark proposed provides interesting results for selecting optimal DAs in order to perform stable and anthropomorphic grasps.ca_CA
dc.format.extent13 p.ca_CA
dc.format.mimetypeapplication/pdfca_CA
dc.language.isoengca_CA
dc.publisherOxford University Pressca_CA
dc.relation.isPartOfJournal of Computational Design and Engineering, 2022, 9(2), 330–342ca_CA
dc.rights©The Author(s) 2022. Published by Oxford University Press on behalf of the Society for Computational Design and Engineering. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.comca_CA
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/ca_CA
dc.subjectartificial hand anthropomorphismca_CA
dc.subjectbenchmarkingca_CA
dc.subjectgrasping simulationca_CA
dc.subjectprosthetic hand designca_CA
dc.titleBenchmarking anthropomorphic hands through grasping simulationsca_CA
dc.typeinfo:eu-repo/semantics/articleca_CA
dc.identifier.doihttps://doi.org/10.1093/jcde/qwac002
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_CA
dc.type.versioninfo:eu-repo/semantics/publishedVersionca_CA
project.funder.nameMinisterio de Economía y Competitividad (Spain)ca_CA
project.funder.nameUniversitat Jaume Ica_CA
project.funder.nameGeneralitat Valencianaca_CA
oaire.awardNumberBES-2015–076005ca_CA
oaire.awardNumberDPI2014-60635-Rca_CA
oaire.awardNumberDPI2017-89910-Rca_CA
oaire.awardNumberUJI-B2017-70ca_CA
oaire.awardNumberGV/2018/125ca_CA
oaire.awardNumberPID2020-118021RB-100ca_CA
oaire.awardNumberMICIN/AEI/10.13039/501100011033ca_CA


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©The Author(s) 2022. Published by Oxford University Press on behalf of the Society for Computational Design and Engineering. This is an Open Access
article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/),
which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial
re-use, please contact journals.permissions@oup.com
Excepto si se señala otra cosa, la licencia del ítem se describe como: ©The Author(s) 2022. Published by Oxford University Press on behalf of the Society for Computational Design and Engineering. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com