Journal article Open Access
Albini Alessandro;
Giorgio Cannata
<?xml version='1.0' encoding='UTF-8'?> <record xmlns="http://www.loc.gov/MARC21/slim"> <leader>00000nam##2200000uu#4500</leader> <datafield tag="041" ind1=" " ind2=" "> <subfield code="a">eng</subfield> </datafield> <datafield tag="653" ind1=" " ind2=" "> <subfield code="a">tactile sensing, robot skin, human robot interaction</subfield> </datafield> <controlfield tag="005">20200311202024.0</controlfield> <controlfield tag="001">3706665</controlfield> <datafield tag="700" ind1=" " ind2=" "> <subfield code="u">University of Genoa</subfield> <subfield code="0">(orcid)0000-0001-7932-5411</subfield> <subfield code="a">Giorgio Cannata</subfield> </datafield> <datafield tag="856" ind1="4" ind2=" "> <subfield code="s">5050158</subfield> <subfield code="z">md5:6f0e43d7291d99e5372d0e9f2b56f1ce</subfield> <subfield code="u">https://zenodo.org/record/3706665/files/Pressure Distribution Classification and Segmentation of Human Hands in Contact with the Robot Body.pdf</subfield> </datafield> <datafield tag="542" ind1=" " ind2=" "> <subfield code="l">open</subfield> </datafield> <datafield tag="260" ind1=" " ind2=" "> <subfield code="c">2020-03-10</subfield> </datafield> <datafield tag="909" ind1="C" ind2="O"> <subfield code="p">openaire</subfield> <subfield code="p">user-collaborate_project</subfield> <subfield code="o">oai:zenodo.org:3706665</subfield> </datafield> <datafield tag="100" ind1=" " ind2=" "> <subfield code="u">University of Genoa</subfield> <subfield code="0">(orcid)0000-0003-1562-7044</subfield> <subfield code="a">Albini Alessandro</subfield> </datafield> <datafield tag="245" ind1=" " ind2=" "> <subfield code="a">Pressure Distribution Classification and Segmentation of Human Hands in Contact with the Robot Body</subfield> </datafield> <datafield tag="980" ind1=" " ind2=" "> <subfield code="a">user-collaborate_project</subfield> </datafield> <datafield tag="536" ind1=" " ind2=" "> <subfield code="c">820767</subfield> <subfield code="a">Co-production CeLL performing Human-Robot Collaborative AssEmbly</subfield> </datafield> <datafield tag="540" ind1=" " ind2=" "> <subfield code="u">https://creativecommons.org/licenses/by/4.0/legalcode</subfield> <subfield code="a">Creative Commons Attribution 4.0 International</subfield> </datafield> <datafield tag="650" ind1="1" ind2="7"> <subfield code="a">cc-by</subfield> <subfield code="2">opendefinition.org</subfield> </datafield> <datafield tag="520" ind1=" " ind2=" "> <subfield code="a"><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></subfield> </datafield> <datafield tag="024" ind1=" " ind2=" "> <subfield code="a">10.1177/0278364920907688</subfield> <subfield code="2">doi</subfield> </datafield> <datafield tag="980" ind1=" " ind2=" "> <subfield code="a">publication</subfield> <subfield code="b">article</subfield> </datafield> </record>
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