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Cyber-Physical System Intelligence

  • 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.

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Metadaten
Author:Tim Niemueller, Frederik Zwilling, Gerhard Lakemeyer, Matthias Löbach, Sebastian Reuter, Sabina Jeschke, Alexander FerreinORCiD
DOI:https://doi.org/10.1007/978-3-319-42559-7_17
ISBN:978-3-319-42559-7
Parent Title (English):Industrial Internet of Things
Publisher:Springer
Place of publication:Cham
Document Type:Part of a Book
Language:English
Year of Completion:2017
Date of the Publication (Server):2017/12/13
Tag:Autonomous mobile robots; Industry 4.0; Multi-robot systems; RoboCup; Smart factory
First Page:447
Last Page:472
Note:
Springer Series in Wireless Technology
Zugriffsart:campus
Institutes:FH Aachen / Fachbereich Elektrotechnik und Informationstechnik
FH Aachen / MASKOR Institut für Mobile Autonome Systeme und Kognitive Robotik
collections:Verlag / Springer