A knowledge base for learning probabilistic decision making from human demonstrations by a multimodal service robot

Sven R. Schmidt-Rohr*, Gerhard Dirschl, Pascal Meissner, Rüdiger Dillmann

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

This paper presents a description logic based system to store and retrieve knowledge used in models for autonomous probabilistic decision making by multimodal service robots. These models are mainly generated by observation and analysis of humans performing tasks, the programming by demonstration methodology. As formal model representation, partially observable Markov decision processes (POMDPs) are utilized as they are a well understood formal framework for decision making considering real world uncertainty in both perception and execution. The approach presented here deals with aspects of organizing knowledge which cannot be retrieved from user demonstrations or which is valid beyond a single task. It is shown how use it in the process of model generation on a real service robot.

Original languageEnglish
Title of host publicationIEEE 15th International Conference on Advanced Robotics
Subtitle of host publicationNew Boundaries for Robotics, ICAR 2011
Pages235-240
Number of pages6
DOIs
Publication statusPublished - 28 Dec 2011
EventIEEE 15th International Conference on Advanced Robotics: New Boundaries for Robotics, ICAR 2011 - Tallinn, Estonia
Duration: 20 Jun 201123 Jun 2011

Publication series

NameIEEE 15th International Conference on Advanced Robotics: New Boundaries for Robotics, ICAR 2011

Conference

ConferenceIEEE 15th International Conference on Advanced Robotics: New Boundaries for Robotics, ICAR 2011
CountryEstonia
CityTallinn
Period20/06/1123/06/11

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    Schmidt-Rohr, S. R., Dirschl, G., Meissner, P., & Dillmann, R. (2011). A knowledge base for learning probabilistic decision making from human demonstrations by a multimodal service robot. In IEEE 15th International Conference on Advanced Robotics: New Boundaries for Robotics, ICAR 2011 (pp. 235-240). [6088640] (IEEE 15th International Conference on Advanced Robotics: New Boundaries for Robotics, ICAR 2011). https://doi.org/10.1109/ICAR.2011.6088640