@article{dd51d960d49741b88e42e5bed8bf0e34,
title = "Supporting Semantic Capture during Kinesthetic Teaching of Collaborative Industrial Robots",
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.",
author = "Maj Stenmark and Mathias Haage and Topp, {Elin Anna} and Jacek Malec",
year = "2018",
month = apr,
doi = "10.1142/S1793351X18400093",
language = "English",
volume = "12",
pages = "167--186",
journal = "International Journal of Semantic Computing",
issn = "1793-7108",
publisher = "World Scientific Publishing",
number = "1",
}