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2016 | OriginalPaper | Chapter

Gathering and Conceptualizing Plan-Based Robot Activity Experiences

Authors : Vahid Mokhtari, Gi Hyun Lim, Luís Seabra Lopes, Armando J. Pinho

Published in: Intelligent Autonomous Systems 13

Publisher: Springer International Publishing

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Abstract

Learning from experiences is an effective approach to enhance robot’s competence. This paper focuses on developing capabilities for a robot to obtain robot activity experiences and conceptualize the experiences as plan schemata, which are used as heuristics for the robot to make plans in similar situations. The plan-based robot activity experiences are obtained through human-robot interactions where a teaching action from a command-line user interface triggers recording of an experience. To represent human-robot interaction activities, ontologies for experiences and user instructions are integrated into a robot ontology. Recorded experiences are episodic descriptions of the robot’s activities including relevant perceptions of the environment, the goals pursued, successes, and failures. Since the amount of experience data is large, a graph simplification algorithm based on ego networks is investigated to filter out irrelevant information in an experience. Finally, an approach to robot activity conceptualization based on deductive generalization and abstraction is presented. The proposed system was demonstrated in a scenario where a PR2 robot is taught how to “serve a coffee” to a guest, in the EU project RACE.

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previous chapter Human-Robot Collaborative Remote Object Search
next chapter Considerate Behavior of Robots Based on Individual’s Preference
Footnotes
1
RACE is funded by the EU Seventh Framework Program theme FP7-ICT-2011-7, grant agreement No. 287752.
 
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Metadata
Title
Gathering and Conceptualizing Plan-Based Robot Activity Experiences
Authors
Vahid Mokhtari
Gi Hyun Lim
Luís Seabra Lopes
Armando J. Pinho
Copyright Year
2016
Book
Intelligent Autonomous Systems 13

Print ISBN: 978-3-319-08337-7

Electronic ISBN: 978-3-319-08338-4

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-08338-4_72

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