Knowledge and Skill Representations for Robotized Production
Björkelund, Anders LU ; Malec, Jacek LU
; Nilsson, Klas
LU
and Nugues, Pierre
LU
(2011)
18th IFAC World Congress, 2011
p.8999-9004
- Abstract
- Model-based systems in control are a means to utilize efficiently human knowledge and achieve high performance. While models consisting of formalized knowledge are used during the engineering step, running systems usually do not contain a high-level, symbolic representation of the control and most of its properties, typically named numerical parameters. On a system level and beyond the plant data, there is also a need to represent the meaning of the data such that deployment and fault analysis could be augmented with partly automated inference based on the semantics of the data. To that end, we extended the formalized knowledge traditionally used in control to include the control purpose, engineering assumption, quality, involved state... (More)
- Model-based systems in control are a means to utilize efficiently human knowledge and achieve high performance. While models consisting of formalized knowledge are used during the engineering step, running systems usually do not contain a high-level, symbolic representation of the control and most of its properties, typically named numerical parameters. On a system level and beyond the plant data, there is also a need to represent the meaning of the data such that deployment and fault analysis could be augmented with partly automated inference based on the semantics of the data. To that end, we extended the formalized knowledge traditionally used in control to include the control purpose, engineering assumption, quality, involved state machines, and so on. We then represented the control semantics in a format that allows an easier extraction of information using querying and reasoning. It aims at making knowledge in control engineering reusable so that it can be shipped together with the control systems. We implemented prototypes that include automatic conversion of plant data from AutomationML into RDF triples, as well as the automated extraction of control properties, the conversion of parameters, and their storage in the same triple store. Although these techniques are standard within the semantic web community, we believe that our robotic prototypes for semantic control represent a novel approach. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4679225
- author
- Björkelund, Anders
LU
; Malec, Jacek
LU
; Nilsson, Klas
LU
and Nugues, Pierre
LU
- organization
- publishing date
- 2011
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Model-based control, Knowledge representation, System architectures, Autonomous control, Industrial robots
- host publication
- Proceedings of the 18th IFAC World Congress, 2011
- pages
- 5 pages
- publisher
- IFAC
- conference name
- 18th IFAC World Congress, 2011
- conference location
- Milan, Italy
- conference dates
- 2011-08-28 - 2011-09-02
- external identifiers
-
- scopus:84866751878
- ISSN
- 1474-6670
- ISBN
- 978-3-902661-93-7
- DOI
- 10.3182/20110828-6-IT-1002.01053
- language
- English
- LU publication?
- yes
- id
- ef7338b4-d1dd-4705-bd0d-77abc99806d6 (old id 4679225)
- date added to LUP
- 2016-04-01 14:56:33
- date last changed
- 2022-01-28 03:15:34
@inproceedings{ef7338b4-d1dd-4705-bd0d-77abc99806d6,
abstract = {{Model-based systems in control are a means to utilize efficiently human knowledge and achieve high performance. While models consisting of formalized knowledge are used during the engineering step, running systems usually do not contain a high-level, symbolic representation of the control and most of its properties, typically named numerical parameters. On a system level and beyond the plant data, there is also a need to represent the meaning of the data such that deployment and fault analysis could be augmented with partly automated inference based on the semantics of the data. To that end, we extended the formalized knowledge traditionally used in control to include the control purpose, engineering assumption, quality, involved state machines, and so on. We then represented the control semantics in a format that allows an easier extraction of information using querying and reasoning. It aims at making knowledge in control engineering reusable so that it can be shipped together with the control systems. We implemented prototypes that include automatic conversion of plant data from AutomationML into RDF triples, as well as the automated extraction of control properties, the conversion of parameters, and their storage in the same triple store. Although these techniques are standard within the semantic web community, we believe that our robotic prototypes for semantic control represent a novel approach.}},
author = {{Björkelund, Anders and Malec, Jacek and Nilsson, Klas and Nugues, Pierre}},
booktitle = {{Proceedings of the 18th IFAC World Congress, 2011}},
isbn = {{978-3-902661-93-7}},
issn = {{1474-6670}},
keywords = {{Model-based control; Knowledge representation; System architectures; Autonomous control; Industrial robots}},
language = {{eng}},
pages = {{8999--9004}},
publisher = {{IFAC}},
title = {{Knowledge and Skill Representations for Robotized Production}},
url = {{http://dx.doi.org/10.3182/20110828-6-IT-1002.01053}},
doi = {{10.3182/20110828-6-IT-1002.01053}},
year = {{2011}},
}