Supporting Semantic Capture during Kinesthetic Teaching of Collaborative Industrial Robots
Stenmark, Maj LU ; Haage, Mathias LU ; Topp, Elin Anna LU
and Malec, Jacek
LU
(2018)
In International Journal of Semantic Computing
12(1).
p.167-186
- Abstract
- Industrial robot systems being deployed today do not contain domain knowledge to aid robot operators in setup and operational use. To gather such knowledge in a robotic context requires mechanisms for entering and capturing semantic data. Such mechanisms would allow a system to gradually build a working vocabulary while interacting with the environment and operators, valuable for the bootstrapping system knowledge and ensuring the data collection over time. This paper presents a prototype user interface that assists the kinesthetic teaching mode of a collaborative industrial robot, allowing for the capture of semantic information while working with the robot in day-to-day use. Two modalities, graphical point-and-click and natural language,... (More)
- Industrial robot systems being deployed today do not contain domain knowledge to aid robot operators in setup and operational use. To gather such knowledge in a robotic context requires mechanisms for entering and capturing semantic data. Such mechanisms would allow a system to gradually build a working vocabulary while interacting with the environment and operators, valuable for the bootstrapping system knowledge and ensuring the data collection over time. This paper presents a prototype user interface that assists the kinesthetic teaching mode of a collaborative industrial robot, allowing for the capture of semantic information while working with the robot in day-to-day use. Two modalities, graphical point-and-click and natural language, support capture of semantic context and the building of a working vocabulary of the environment while modifying or creating robot programs. A semantic capture experiment illustrates the approach.
(Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/dd51d960-d497-41b8-8e42-e5bed8bf0e34
- author
- Stenmark, Maj
LU
; Haage, Mathias
LU
; Topp, Elin Anna
LU
and Malec, Jacek
LU
- organization
- publishing date
- 2018-04
- type
- Contribution to journal
- publication status
- published
- subject
- in
- International Journal of Semantic Computing
- volume
- 12
- issue
- 1
- pages
- 20 pages
- publisher
- World Scientific Publishing
- external identifiers
-
- scopus:85051499914
- ISSN
- 1793-7108
- DOI
- 10.1142/S1793351X18400093
- project
- SARAFun—Smart Assembly Robot with Advanced FUNctionalities
- language
- English
- LU publication?
- yes
- id
- dd51d960-d497-41b8-8e42-e5bed8bf0e34
- date added to LUP
- 2017-06-12 14:10:26
- date last changed
- 2022-04-25 00:34:50
@article{dd51d960-d497-41b8-8e42-e5bed8bf0e34,
abstract = {{Industrial robot systems being deployed today do not contain domain knowledge to aid robot operators in setup and operational use. To gather such knowledge in a robotic context requires mechanisms for entering and capturing semantic data. Such mechanisms would allow a system to gradually build a working vocabulary while interacting with the environment and operators, valuable for the bootstrapping system knowledge and ensuring the data collection over time. This paper presents a prototype user interface that assists the kinesthetic teaching mode of a collaborative industrial robot, allowing for the capture of semantic information while working with the robot in day-to-day use. Two modalities, graphical point-and-click and natural language, support capture of semantic context and the building of a working vocabulary of the environment while modifying or creating robot programs. A semantic capture experiment illustrates the approach.<br/>}},
author = {{Stenmark, Maj and Haage, Mathias and Topp, Elin Anna and Malec, Jacek}},
issn = {{1793-7108}},
language = {{eng}},
number = {{1}},
pages = {{167--186}},
publisher = {{World Scientific Publishing}},
series = {{International Journal of Semantic Computing}},
title = {{Supporting Semantic Capture during Kinesthetic Teaching of Collaborative Industrial Robots}},
url = {{http://dx.doi.org/10.1142/S1793351X18400093}},
doi = {{10.1142/S1793351X18400093}},
volume = {{12}},
year = {{2018}},
}