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	<pub:InProceedings rdf:about="http://ebiquity.umbc.edu/paper/html/id/901/Learning-from-Human-Robot-Interactions-in-Modeled-Scenes">
		<rdfs:label><![CDATA[Learning from Human-Robot Interactions in Modeled Scenes]]></rdfs:label>
		<pub:title><![CDATA[Learning from Human-Robot Interactions in Modeled Scenes]]></pub:title>
		<pub:publishedOn rdf:datatype="&xsd;dateTime">2019-07-28T00:00:00-05:00</pub:publishedOn>
		<pub:abstract><![CDATA[There is increasing interest in using robots in simulation to understand and improve human-robot interaction (HRI). At the same time, the use of simulated settings to gather training data promises to help address a major data bottleneck in allowing robots to take advantage of powerful machine learning approaches. In this paper, we describe a prototype system that combines the robot operating system (ROS), the simulator Gazebo, and the Unity game engine to create human-robot interaction scenarios. A person can engage with the scenario using a monitor wall, allowing simultaneous collection of realistic sensor data and traces of human actions.]]></pub:abstract>
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<figure><img src="https://ebiquity.umbc.edu/blogger/wp-content/uploads/2020/05/Screen-Shot-2020-05-31-at-11.04.48-AM.png" alt="" style="width:100%" /></figure>]]></pub:note>
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		<pub:tag><![CDATA[robotics]]></pub:tag>
		<pub:booktitle><![CDATA[ACM SIGGRAPH 2019 Posters]]></pub:booktitle>
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