Conference paper Open Access

Human-robot complementarity: Learning each other and collaborating

Dagioglou, Maria; Konstantopoulos, Stasinos


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        <foaf:name>Dagioglou, Maria</foaf:name>
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        <foaf:name>Konstantopoulos, Stasinos</foaf:name>
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    <dct:title>Human-robot complementarity: Learning each other and collaborating</dct:title>
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    <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#gYear">2017</dct:issued>
    <dcat:keyword>Human-robot interaction</dcat:keyword>
    <dcat:keyword>Human-robot collaboration</dcat:keyword>
    <dcat:keyword>Human intentions</dcat:keyword>
    <dcat:keyword>Robot intentions</dcat:keyword>
    <dcat:keyword>Assistive teleoperation</dcat:keyword>
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    <dct:description>&lt;p&gt;As robot capabilities increase, the complexity of controlling and manipulating them becomes complex and cumbersome making intuitive Human-Robot Interaction all the more necessary for seamless human-robot collaboration. In this paper, we look into the ability of collaborators to understand each other’s intentions and act accordingly in order to promote the collaboration. We focus on scenarios that human intentions are communicated through movement. In order to endow robots with understanding of human intentions, as well as with robot behaviours that humans interpret correctly, we need to look at mechanisms humans recruit to perceive and communicate intentions. We then need to distil the essence of these mechanisms so that they can be applied to completely non-anthropomorphic robot collaborators.&lt;/p&gt;</dct:description>
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