NDLI: Using Physical Demonstrations, Background Knowledge and Vocal Comments for Task Learning

Content Provider	IEEE Xplore Digital Library
Author	Pardowitz, M. Zollner, R. Knoop, S. Dillmann, R.
Copyright Year	2006
Description	Author affiliation: Inst. of Comput. Sci. & Eng., Karlsruhe Univ. (Pardowitz, M.; Zollner, R.; Knoop, S.; Dillmann, R.)
Abstract	Robot assistants in the same environment with humans have to interact with humans and learn or at least adapt to individual human needs. One of the core abilities is learning from human demonstrations, were the robot is supposed to observe the execution of a task, acquire task knowledge and reproduce it. In this paper, a system to interpret and reason over demonstrations of household tasks is presented. The focus is on the model based representation of manipulation tasks, which serves as a basis for reasoning over the acquired task knowledge. The aim of the reasoning is to condense and interconnect the knowledge. A measure for the assessment of information content of task features is introduced that relies both on general background knowledge as well as task-specific knowledge gathered from the user demonstrations. Beside the autonomous information estimation of features, speech comments during the execution, pointing out the relevance of features are considered as well
Starting Page	322
Ending Page	327
File Size	586713
Page Count	6
File Format	PDF
ISBN	1424402581
DOI	10.1109/IROS.2006.282506
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-10-09
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Learning systems Intelligent robots Computer science Knowledge engineering Human robot interaction Speech Service robots Robot programming Monitoring Humanoid robots
Content Type	Text
Resource Type	Article

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