Cyber-Physical System Intelligence. Niemueller, T., Zwilling, F., Lakemeyer, G., Löbach, M., Reuter, S., Jeschke, S., & Ferrein, A. In Jeschke, S., Brecher, C., Song, H., & Rawat, D. B., editors, Industrial Internet of Things: Cybermanufacturing Systems, of Springer Series in Wireless Technology, pages 447–472. Springer International Publishing, 2017. ![Cyber-Physical System Intelligence [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Cyber-physical systems are ever more common in manufacturing industries. Increasing their autonomy has been declared an explicit goal, for example, as part of the Industry 4.0 vision. To achieve this system intelligence, principled and software-driven methods are required to analyze sensing data, make goal-directed decisions, and eventually execute and monitor chosen tasks. In this chapter, we present a number of knowledge-based approaches to these problems and case studies with in-depth evaluation results of several different implementations for groups of autonomous mobile robots performing in-house logistics in a smart factory. We focus on knowledge-based systems because besides providing expressive languages and capable reasoning techniques, they also allow for explaining how a particular sequence of actions came about, for example, in the case of a failure.
@incollection{niemueller_cyber-physical_2017,
series = {Springer {Series} in {Wireless} {Technology}},
title = {Cyber-{Physical} {System} {Intelligence}},
isbn = {978-3-319-42559-7},
url = {https://doi.org/10.1007/978-3-319-42559-7_17},
abstract = {Cyber-physical systems are ever more common in manufacturing industries. Increasing their autonomy has been declared an explicit goal, for example, as part of the Industry 4.0 vision. To achieve this system intelligence, principled and software-driven methods are required to analyze sensing data, make goal-directed decisions, and eventually execute and monitor chosen tasks. In this chapter, we present a number of knowledge-based approaches to these problems and case studies with in-depth evaluation results of several different implementations for groups of autonomous mobile robots performing in-house logistics in a smart factory. We focus on knowledge-based systems because besides providing expressive languages and capable reasoning techniques, they also allow for explaining how a particular sequence of actions came about, for example, in the case of a failure.},
language = {en},
urldate = {2018-12-17},
booktitle = {Industrial {Internet} of {Things}: {Cybermanufacturing} {Systems}},
publisher = {Springer International Publishing},
author = {Niemueller, Tim and Zwilling, Frederik and Lakemeyer, Gerhard and Löbach, Matthias and Reuter, Sebastian and Jeschke, Sabina and Ferrein, Alexander},
editor = {Jeschke, Sabina and Brecher, Christian and Song, Houbing and Rawat, Danda B.},
year = {2017},
doi = {10.1007/978-3-319-42559-7_17},
keywords = {And scheduling, Automated reasoning, Autonomous mobile robots, Industry 4.0, Multi-robot systems, Planning, RoboCup, Smart factory, Task coordination},
pages = {447--472}
}
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