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Open AccessReview

Integrations between Autonomous Systems and Modern Computing Techniques: A Mini Review

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Department of Mechanical engineering, Yuan Ze University, Taoyuan 32003, Taiwan
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Department of Electronic and Computer Engineering, Brunel University London, Uxbridge UB8 3PH, UK
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Authors to whom correspondence should be addressed.
Sensors 2019, 19(18), 3897; https://doi.org/10.3390/s19183897
Received: 12 July 2019 / Revised: 26 August 2019 / Accepted: 29 August 2019 / Published: 10 September 2019
The emulation of human behavior for autonomous problem solving has been an interdisciplinary field of research. Generally, classical control systems are used for static environments, where external disturbances and changes in internal parameters can be fully modulated before or neglected during operation. However, classical control systems are inadequate at addressing environmental uncertainty. By contrast, autonomous systems, which were first studied in the field of control systems, can be applied in an unknown environment. This paper summarizes the state of the art autonomous systems by first discussing the definition, modeling, and system structure of autonomous systems and then providing a perspective on how autonomous systems can be integrated with advanced resources (e.g., the Internet of Things, big data, Over-the-Air, and federated learning). Finally, what comes after reaching full autonomy is briefly discussed. View Full-Text
Keywords: autonomous; intelligent control system; machine learning; IoT; big data; federated learning autonomous; intelligent control system; machine learning; IoT; big data; federated learning
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Chen, J.; Abbod, M.; Shieh, J.-S. Integrations between Autonomous Systems and Modern Computing Techniques: A Mini Review. Sensors 2019, 19, 3897.

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