Inferring Robot Morphology from Observation of Unscripted Movement

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dc.contributor.authorBell, Neil
dc.contributor.authorSeipp, Brian
dc.contributor.authorOates, J. Tim
dc.contributor.authorMatuszek, Cynthia
dc.date.accessioned2019-07-09T15:10:57Z
dc.date.available2019-07-09T15:10:57Z
dc.date.issued2019-05
dc.description.abstractTask sharing between heterogeneous robots currently requires a priori capability knowledge, a shared communication protocol, or a centralized planner. However, in practice, when two robots are brought together, the effort required to construct shared action and structure models is significant. In this paper, we describe our approach to determining the kinematic model of a robot based purely on observation of unscripted movement. We describe construction of large-scale data simulating low-cost RGB-D camera output, and application of two different RNN-based methods to the learning problem. Our results suggest that this is an efficient and effective way to determine a robot’s morphological structure without requiring communication or pre-existing knowledge of its capabilities.en_US
dc.description.urihttp://iral.cs.umbc.edu/Pubs/BellICRA2019.pdfen_US
dc.format.extent7 pagesen_US
dc.genreconference papers and proceedings preprintsen_US
dc.identifierdoi:10.13016/m2tdyv-pzyj
dc.identifier.citationNeil Bell, et.al, Inferring Robot Morphology from Observation of Unscripted Movement, 2019 IEEE International Conference on Robotics and Automation (ICRA), http://iral.cs.umbc.edu/Pubs/BellICRA2019.pdfen_US
dc.identifier.urihttp://hdl.handle.net/11603/14360
dc.language.isoen_USen_US
dc.publisherIEEE
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
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.rights© 2019 IEEE
dc.subjecttask sharing between heterogeneous robotsen_US
dc.subjectkinematic modelen_US
dc.subjectlow-cost RGB-D camera outputen_US
dc.subjectInteractive Robotics and Language Lab
dc.subjecttask sharing between heterogeneous robots
dc.titleInferring Robot Morphology from Observation of Unscripted Movementen_US
dc.typeTexten_US

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