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dc.contributor.authorPuls, Stephan*
dc.date.accessioned2021-02-12T03:40:38Z
dc.date.available2021-02-12T03:40:38Z
dc.date.issued2014*
dc.date.submitted2019-07-30 20:02:00*
dc.identifier35071*
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/59442
dc.description.abstractIn the proposed system the environment of an industrial robot is captured through algorithms of machine learning. Thus, objects and human actions are determined. Based on semantic analysis situational knowledge is inferred and dynamic risk assessment as well as robotic behaviour are concluded. Consequently, this provides the foundation for a reactive robot system for achieving efficient and safe human-robot-cooperation.*
dc.languageGerman*
dc.subjectQA75.5-76.95*
dc.subject.otherimage processing*
dc.subject.otherMaschinelles Lernen*
dc.subject.otherBildverarbeitung*
dc.subject.othersemantic analysis*
dc.subject.otherSemantische Analyse*
dc.subject.otherSituationsverstehen*
dc.subject.othermachine learning*
dc.subject.othersituation awareness*
dc.subject.otherRobotik*
dc.subject.otherRobotics*
dc.titleSituationsverstehen für die Risikobeurteilung bei der Mensch-Roboter-Kooperation*
dc.typebook
oapen.identifier.doi10.5445/KSP/1000044584*
oapen.relation.isPublishedBy68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2*
virtual.oapen_relation_isPublishedBy.publisher_nameKIT Scientific Publishing
virtual.oapen_relation_isPublishedBy.publisher_websitehttp://www.ksp.kit.edu/
oapen.relation.isbn9783731502999*
oapen.pagesXII, 169 p.*


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Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by-sa/4.0/