Memmesheimer2020RIB

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Autor:
Memmesheimer, Raphael, https://www.uni-koblenz-landau.de/de/koblenz/fb4/icv/agpaulus/agas-team/raphael_folder
Kramer, Ivanna
Seib, Viktor, https://www.uni-koblenz-landau.de/de/koblenz/fb4/icv/agpaulus/agas-team/alumni_f/vseib/vseib
Theisen, Nick
Paulus, Dietrich
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Titel:Robotic Imitation by Markerless Visual Observation and Semantic Associations
Buchtitel:2020 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)
Verlag:
IEEE,
Organisation:
IEEE,
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Monat:4
Jahr:2020
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Abstrakt:In this paper we present an approach for learning to imitate human behavior on a semantic level by markerless visual observation. We analyze a set of spatial constraints on human pose data extracted using convolutional pose machines and object information extracted from 2D image sequences. A scene analysis, based on an ontology of objects and affordances, is combined with continuous human pose estimation and spatial object relations. Using a set of constraints we associate the observed human actions with a set of executable robot commands. We demonstrate our approach in a kitchen task, where the robot learns to prepare a meal.
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weitere Felder:
isbn = 978-1-7281-7079-4
doi = 10.1109/ICARSC49921.2020.9096123
Literaturschlüssel:Memmesheimer2020RIB
Beteiligte Einrichtungen:FB 4: Informatik, Arbeitsgruppe Aktives Sehen
Literaturtyp:inproceedings