1 Ocak 2017 Dergi makalesi Açık Erişim

Muhammad, Jawad; Altun, Halis; Abo-Serie, Essam

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  <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/46557</identifier>
  <creators>
    <creator>
      <creatorName>Muhammad, Jawad</creatorName>
      <givenName>Jawad</givenName>
      <familyName>Muhammad</familyName>
      <affiliation>Mevlana Univ, Konya, Konya, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Altun, Halis</creatorName>
      <givenName>Halis</givenName>
      <familyName>Altun</familyName>
      <affiliation>Karatay Univ, Konya, Konya, Turkey</affiliation>
    </creator>
    <creator>
      <creatorName>Abo-Serie, Essam</creatorName>
      <givenName>Essam</givenName>
      <familyName>Abo-Serie</familyName>
      <affiliation>Mevlana Univ, Konya, Konya, Turkey</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Welding Seam Profiling Techniques Based On Active Vision Sensing For Intelligent Robotic Welding</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2017</publicationYear>
  <dates>
    <date dateType="Issued">2017-01-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Journal article</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/46557</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1007/s00170-016-8707-0</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
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  <descriptions>
    <description descriptionType="Abstract">Intelligent robotic welding involves replicating the role of a manual professional welder to adaptively control the welding process. This is necessary to achieve accurate, fast and high-quality welding process in addition to the challenging factors for humans to operate in the welding environment. Therefore, robotic welding exists since the early days of robotics and it is still an active research area. This is why there have been numerous researches in this area for a very long time. Among various techniques proposed by researchers for the adaptive control of the robotic welding process, vision-based control is the most popular due to its non-invasiveness. Therefore, in this paper, we review, analyse and categorise the proposed vision-based techniques with the aim of covering the different image processing and feature extraction aspect of the techniques. The focus is mainly on the active vision system where various image processing techniques have been utilised in extracting the welding seam features. The challenges and difficulties to extract seam features in active vision system have been highlighted. The trends and new approaches have been indicated in order to provide a comprehensive source for researchers who are planning to carry out research related to the intelligent robot vision techniques for welding automation.</description>
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