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Robot Experience Stories: first person generation of robotic task narratives in SitLog

Abstract : What if service robots could tell the story of the task they've just realized like a story? The aim of our work is to provide service robots with natural language capabilities to produce a Robot Experience Story for its human interlocutors. Robxp stories are narratives composed of the robot's holistic perception of a recently performed task: navigation, visual perceptions and action descriptions. We contribute with a narrate dialog model specifying the composition of situations necessary for a service robot to transform its task history record into a narrative knowledge representation. We provide SitLog algorithms allowing to analyze the robot's situation and behaviors sequence in order to generate a robxp story of the task. Both the dialogue model and the algorithms can be embedded as compositional behaviors in any other SitLog task structure. We instantiated our model into the Golem service robot framework on an experimental task. We believe Robxp stories generation could be integrated as a standard behavior for more complex service robot tasks.
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Contributor : Jorge Garcia Flores Connect in order to contact the contributor
Submitted on : Friday, October 29, 2021 - 2:05:33 PM
Last modification on : Monday, August 8, 2022 - 5:38:05 PM
Long-term archiving on: : Monday, January 31, 2022 - 9:36:03 AM

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Jorge Garcia Flores, Iván Meza, Émilie Colin, Claire Gardent, Aldo Gangemi, et al.. Robot Experience Stories: first person generation of robotic task narratives in SitLog. Journal of Intelligent and Fuzzy Systems, IOS Press, 2018, Intelligent and Fuzzy Systems applied to Language & Knowledge Engineering, 34 (5), pp.3291-3300. ⟨10.3233/JIFS-169511⟩. ⟨hal-03408974⟩



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