Learning from human-robot interactions in modeled scenes

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dc.contributor.authorMurnane, Mark
dc.contributor.authorBreitmeyer, Max
dc.contributor.authorFerraro, Francis
dc.contributor.authorMatuszek, Cynthia
dc.contributor.authorEngel, Don
dc.date.accessioned2021-04-30T15:20:27Z
dc.date.available2021-04-30T15:20:27Z
dc.descriptionSIGGRAPH '19: ACM SIGGRAPH 2019 Posters, July 2019, Article No.1 Pages 1–2en_US
dc.description.abstractThere 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.en_US
dc.description.sponsorshipThis material is based upon work supported by the National Science Foundation under Grants No. 1531491 and 1428204. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. Support was also provided for this work by the Next Century Corporation.en_US
dc.description.urihttps://dl.acm.org/doi/abs/10.1145/3306214.3338546en_US
dc.format.extent2 pagesen_US
dc.genreconference papers and proceedingsen_US
dc.identifierdoi:10.13016/m2wosn-jvmw
dc.identifier.citationMark Murnane, Max Breitmeyer, Francis Ferraro, Cynthia Matuszek, and Don Engel. 2019. Learning from human-robot interactions in modeled scenes. In ACM SIGGRAPH 2019 Posters (SIGGRAPH '19). Association for Computing Machinery, New York, NY, USA, Article 1, 1–2. DOI:https://doi.org/10.1145/3306214.3338546en_US
dc.identifier.urihttps://doi.org/10.1145/3306214.3338546
dc.identifier.urihttp://hdl.handle.net/11603/21408
dc.language.isoen_USen_US
dc.publisherACMen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Office for the Vice President of Research
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Student Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.subjectRoboticsen_US
dc.subjectVirtual Realityen_US
dc.subjectMachine Learningen_US
dc.titleLearning from human-robot interactions in modeled scenesen_US
dc.typeTexten_US

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