Conference paper Open Access

Online Prediction for Safe Human-Robot Collaboration: A Model of the Human Arm

Binchi, Jacopo; Mangeruca, Leonardo; Rucco, Matteo; Orlando, Ferrante; Minissale, Alfio; Abba', Fabio Francesco


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  <identifier identifierType="DOI">10.5281/zenodo.3901416</identifier>
  <creators>
    <creator>
      <creatorName>Binchi, Jacopo</creatorName>
      <givenName>Jacopo</givenName>
      <familyName>Binchi</familyName>
      <affiliation>United Technologies Research Center</affiliation>
    </creator>
    <creator>
      <creatorName>Mangeruca, Leonardo</creatorName>
      <givenName>Leonardo</givenName>
      <familyName>Mangeruca</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-0532-5712</nameIdentifier>
      <affiliation>United Technologies Research Center</affiliation>
    </creator>
    <creator>
      <creatorName>Rucco, Matteo</creatorName>
      <givenName>Matteo</givenName>
      <familyName>Rucco</familyName>
      <affiliation>United Technologies Research Center</affiliation>
    </creator>
    <creator>
      <creatorName>Orlando, Ferrante</creatorName>
      <givenName>Ferrante</givenName>
      <familyName>Orlando</familyName>
      <affiliation>United Technologies Research Center</affiliation>
    </creator>
    <creator>
      <creatorName>Minissale, Alfio</creatorName>
      <givenName>Alfio</givenName>
      <familyName>Minissale</familyName>
      <affiliation>COMAU SpA - Robotics and Automation Products</affiliation>
    </creator>
    <creator>
      <creatorName>Abba', Fabio Francesco</creatorName>
      <givenName>Fabio Francesco</givenName>
      <familyName>Abba'</familyName>
      <affiliation>COMAU SpA - Robotics and Automation Products</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Online Prediction for Safe Human-Robot Collaboration: A Model of the Human Arm</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2020</publicationYear>
  <subjects>
    <subject>robotics, predictive model, human dynamics, reachability analysis</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2020-09-29</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="ConferencePaper"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3901416</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="Cites" resourceTypeGeneral="JournalArticle">10.1109/TASE.2017.2707129</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3901415</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/sherlock_h2020_project</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode">Creative Commons Attribution Non Commercial No Derivatives 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Traditionally safety in industrial manufacturing environments has been addressed by rigid separation between robots and human operators. With the advent of new technologies and the transition of production to industry 4.0, a more flexible approach to manufacturing is pursued to achieve higher productivity, where robots and human operators are allowed to collaborate and interact. This transformation leads to overcoming traditional safety procedures and the development of new safety-assuring technologies for the minimization of risks connected with human robot collaboration. In this work we focus on the prediction of movements of operators&amp;rsquo; upper torso and arms by developing a method which combines data driven methodologies with formal methods. The approach is based on a predictive model of human motion compared against the planned robot trajectory and online monitoring of satisfaction of safety requirements with formal methods. We provide an early assessment of the robustness of the proposed method with results from simulations in a virtual environment.&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/100010661</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/820689/">820689</awardNumber>
      <awardTitle>Seamless and safe human - centred robotic applications for novel collaborative workplaces</awardTitle>
    </fundingReference>
  </fundingReferences>
</resource>
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