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dc.contributor.authorRubert, Carlos
dc.contributor.authorLeón Pinzón, Beatriz Elena
dc.contributor.authorMorales Escrig, Antonio
dc.contributor.authorSancho-Bru, Joaquin L.
dc.date.accessioned2017-07-13T07:12:04Z
dc.date.available2017-07-13T07:12:04Z
dc.date.issued2017-05
dc.identifier.citationRUBERT, Carlos, et al. Characterisation of Grasp Quality Metrics. Journal of Intelligent & Robotic Systems, 2017, p. 1-24.ca_CA
dc.identifier.urihttp://hdl.handle.net/10234/168278
dc.description.abstractRobot grasp quality metrics are used to evaluate, compare and select robotic grasp configurations. Many of them have been proposed based on a diversity of underlying principles and to assess different aspects of the grasp configurations. As a consequence, some of them provide similar information but other can provide completely different assessments. Combinations of metrics have been proposed in order to provide global indexes, but these attempts have shown the difficulties of merging metrics with different numerical ranges and even physical units. All these studies have raised the need of a deeper knowledge in order to determine independent grasp quality metrics which enable a global assessment of a grasp, and a way to combine them. This paper presents an exhaustive study in order to provide numerical evidence for these issues. Ten quality metrics are used to evaluate a set of grasps planned by a simulator for 7 different robot hands over a set of 126 object models. Three statistical analysis, namely, variability, correlation and sensitivity, are performed over this extensive database. Results and graphs presented allow to set practical thresholds for each quality metric, select independent metrics, and determine the robustness of each metric,providing a reliability indicator under pose uncertainty. The results from this paper are intended to serve as guidance for practical use of quality metrics by researchers on grasp planning algorithms.ca_CA
dc.format.extent23 p.ca_CA
dc.format.mimetypeapplication/pdfca_CA
dc.language.isoengca_CA
dc.publisherSpringer Verlagca_CA
dc.relation.isPartOfIntell Robot Syst (2017)ca_CA
dc.rights© Springer Science+Business Media Dordrecht 2017ca_CA
dc.subjectgrasp planningca_CA
dc.subjectmultifingered handsca_CA
dc.subjectquality metricsca_CA
dc.titleCharacterisation of Grasp Quality Metricsca_CA
dc.typeinfo:eu-repo/semantics/articleca_CA
dc.identifier.doihttp://dx.doi.org/10.1007/s10846-017-0562-1
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_CA
dc.relation.publisherVersionhttps://link.springer.com/article/10.1007/s10846-017-0562-1#Bib1ca_CA


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