A CPS-Based Architecture for Mobile Robotics: Design, Integration, and Localisation Experiments
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| Veröffentlicht in: | Sensors vol. 25, no. 18 (2025), p. 5715-5742 |
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MDPI AG
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| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231630 |2 nlm | ||
| 100 | 1 | |a Líšková Dominika |u Department of Cybernetics and Artificial Intelligence, Faculty of Electrical Engineering and Informatics, Technical University of Košice, Letná 9, 042 00 Košice, Slovakia | |
| 245 | 1 | |a A CPS-Based Architecture for Mobile Robotics: Design, Integration, and Localisation Experiments | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a This paper presents the design and implementation of a mobile robotic platform modelled as a layered Cyber–Physical System (CPS). Inspired by architectures commonly used in industrial Distributed Control Systems (DCSs) and large-scale scientific infrastructures, the proposed system incorporates modular hardware, distributed embedded control, and multi-level coordination. The robotic platform, named MapBot, is structured according to a five-layer CPS model encompassing component, control, coordination, supervisory, and management layers. This structure facilitates modular development, system scalability, and integration of advanced features such as a digital twin. The platform is implemented using embedded computing elements, diverse sensors, and communication protocols including Ethernet and I2C. The system operates within the ROS2 framework, supporting flexible task distribution across processing nodes. As a use case, two localization techniques—Adaptive Monte Carlo Localization (AMCL) and pose graph SLAM—are deployed and evaluated, highlighting the performance trade-offs in map quality, update frequency, and computational load. The results demonstrate that CPS-based design principles offer clear advantages for robotic platforms in terms of modularity, maintainability, and real-time integration. The proposed approach can be generalised for other robotic or mechatronic systems requiring structured, layered control and embedded intelligence. | |
| 653 | |a Software | ||
| 653 | |a Embedded systems | ||
| 653 | |a Communication | ||
| 653 | |a Sensors | ||
| 653 | |a Decision making | ||
| 653 | |a Flexibility | ||
| 653 | |a Robots | ||
| 653 | |a Distributed control systems | ||
| 653 | |a Decentralization | ||
| 653 | |a Design | ||
| 653 | |a Modularity | ||
| 653 | |a Informatics | ||
| 653 | |a Localization | ||
| 653 | |a Fault tolerance | ||
| 653 | |a Robotics | ||
| 700 | 1 | |a Jadlovská Anna |u Department of Cybernetics and Artificial Intelligence, Faculty of Electrical Engineering and Informatics, Technical University of Košice, Letná 9, 042 00 Košice, Slovakia | |
| 700 | 1 | |a Pazdič Filip |u School of Physics and Astronomy, The University of Birmingham, Edgbaston, Birmingham B15 2TT, UK; f.pazdic@bham.ac.uk | |
| 773 | 0 | |t Sensors |g vol. 25, no. 18 (2025), p. 5715-5742 | |
| 786 | 0 | |d ProQuest |t Health & Medical Collection | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3254645680/abstract/embedded/H09TXR3UUZB2ISDL?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3254645680/fulltextwithgraphics/embedded/H09TXR3UUZB2ISDL?source=fedsrch |
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