Journal article Open Access
Albini Alessandro;
Giorgio Cannata
<?xml version='1.0' encoding='utf-8'?> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:adms="http://www.w3.org/ns/adms#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dct="http://purl.org/dc/terms/" xmlns:dctype="http://purl.org/dc/dcmitype/" xmlns:dcat="http://www.w3.org/ns/dcat#" xmlns:duv="http://www.w3.org/ns/duv#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:frapo="http://purl.org/cerif/frapo/" xmlns:geo="http://www.w3.org/2003/01/geo/wgs84_pos#" xmlns:gsp="http://www.opengis.net/ont/geosparql#" xmlns:locn="http://www.w3.org/ns/locn#" xmlns:org="http://www.w3.org/ns/org#" xmlns:owl="http://www.w3.org/2002/07/owl#" xmlns:prov="http://www.w3.org/ns/prov#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xmlns:schema="http://schema.org/" xmlns:skos="http://www.w3.org/2004/02/skos/core#" xmlns:vcard="http://www.w3.org/2006/vcard/ns#" xmlns:wdrs="http://www.w3.org/2007/05/powder-s#"> <rdf:Description rdf:about="https://zenodo.org/record/3706665"> <rdf:type rdf:resource="http://www.w3.org/ns/dcat#Dataset"/> <dct:type rdf:resource="http://purl.org/dc/dcmitype/Text"/> <dct:identifier rdf:datatype="http://www.w3.org/2001/XMLSchema#anyURI">https://zenodo.org/record/3706665</dct:identifier> <foaf:page rdf:resource="https://zenodo.org/record/3706665"/> <dct:creator> <rdf:Description rdf:about="http://orcid.org/0000-0003-1562-7044"> <rdf:type rdf:resource="http://xmlns.com/foaf/0.1/Agent"/> <dct:identifier rdf:datatype="http://www.w3.org/2001/XMLSchema#string">0000-0003-1562-7044</dct:identifier> <foaf:name>Albini Alessandro</foaf:name> <org:memberOf> <foaf:Organization> <foaf:name>University of Genoa</foaf:name> </foaf:Organization> </org:memberOf> </rdf:Description> </dct:creator> <dct:creator> <rdf:Description rdf:about="http://orcid.org/0000-0001-7932-5411"> <rdf:type rdf:resource="http://xmlns.com/foaf/0.1/Agent"/> <dct:identifier rdf:datatype="http://www.w3.org/2001/XMLSchema#string">0000-0001-7932-5411</dct:identifier> <foaf:name>Giorgio Cannata</foaf:name> <org:memberOf> <foaf:Organization> <foaf:name>University of Genoa</foaf:name> </foaf:Organization> </org:memberOf> </rdf:Description> </dct:creator> <dct:title>Pressure Distribution Classification and Segmentation of Human Hands in Contact with the Robot Body</dct:title> <dct:publisher> <foaf:Agent> <foaf:name>Zenodo</foaf:name> </foaf:Agent> </dct:publisher> <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#gYear">2020</dct:issued> <dcat:keyword>tactile sensing, robot skin, human robot interaction</dcat:keyword> <frapo:isFundedBy rdf:resource="info:eu-repo/grantAgreement/EC/H2020/820767/"/> <schema:funder> <foaf:Organization> <dct:identifier rdf:datatype="http://www.w3.org/2001/XMLSchema#string">10.13039/501100000780</dct:identifier> <foaf:name>European Commission</foaf:name> </foaf:Organization> </schema:funder> <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#date">2020-03-10</dct:issued> <dct:language rdf:resource="http://publications.europa.eu/resource/authority/language/ENG"/> <owl:sameAs rdf:resource="https://zenodo.org/record/3706665"/> <adms:identifier> <adms:Identifier> <skos:notation rdf:datatype="http://www.w3.org/2001/XMLSchema#anyURI">https://zenodo.org/record/3706665</skos:notation> <adms:schemeAgency>url</adms:schemeAgency> </adms:Identifier> </adms:identifier> <owl:sameAs rdf:resource="https://doi.org/10.1177/0278364920907688"/> <dct:isPartOf rdf:resource="https://zenodo.org/communities/collaborate_project"/> <dct:description><p>This paper deals with the problem of the recognition of human hand touch by a robot equipped with large area tactile<br> sensors covering its body. This problem is relevant in the domain of physical human-robot interaction for discriminating<br> between human and non-human contacts and to trigger and to drive cooperative tasks or robot motions, or to ensure a<br> safe interaction. The underlying assumption, used in this paper, is that voluntary physical interaction tasks involve hand<br> touch over the robot body, and therefore the capability of recognizing hand contacts is a key element to discriminate a<br> purposive human touch from other types of interaction.<br> The proposed approach is based on a geometric transformation of the tactile data, formed by pressure measurements<br> associated to a non uniform cloud of 3D points (taxels) spread over a non linear manifold corresponding to the robot<br> body, into tactile images representing the contact pressure distribution in 2D. Tactile images can be processed using<br> deep learning algorithms to recognize human hands and to compute the pressure distribution applied by the various<br> hand segments: palm and single fingers.<br> Experimental results, performed on a real robot covered with robot skin, show the effectiveness of the proposed<br> methodology. Moreover, to evaluate its robustness, various types of failures have been simulated. A further analysis<br> concerning the transferability of the system has been performed, considering contacts occurring on a different<br> sensorized robot part.</p></dct:description> <dct:accessRights rdf:resource="http://publications.europa.eu/resource/authority/access-right/PUBLIC"/> <dct:accessRights> <dct:RightsStatement rdf:about="info:eu-repo/semantics/openAccess"> <rdfs:label>Open Access</rdfs:label> </dct:RightsStatement> </dct:accessRights> <dcat:distribution> <dcat:Distribution> <dct:license rdf:resource="https://creativecommons.org/licenses/by/4.0/legalcode"/> <dcat:accessURL rdf:resource="https://zenodo.org/record/3706665"/> </dcat:Distribution> </dcat:distribution> <dcat:distribution> <dcat:Distribution> <dcat:accessURL>https://doi.org/10.1177/0278364920907688</dcat:accessURL> <dcat:byteSize>5050158</dcat:byteSize> <dcat:downloadURL>https://zenodo.org/record/3706665/files/Pressure Distribution Classification and Segmentation of Human Hands in Contact with the Robot Body.pdf</dcat:downloadURL> <dcat:mediaType>application/pdf</dcat:mediaType> </dcat:Distribution> </dcat:distribution> </rdf:Description> <foaf:Project rdf:about="info:eu-repo/grantAgreement/EC/H2020/820767/"> <dct:identifier rdf:datatype="http://www.w3.org/2001/XMLSchema#string">820767</dct:identifier> <dct:title>Co-production CeLL performing Human-Robot Collaborative AssEmbly</dct:title> <frapo:isAwardedBy> <foaf:Organization> <dct:identifier rdf:datatype="http://www.w3.org/2001/XMLSchema#string">10.13039/501100000780</dct:identifier> <foaf:name>European Commission</foaf:name> </foaf:Organization> </frapo:isAwardedBy> </foaf:Project> </rdf:RDF>
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