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|Title:||Integrations between Autonomous System and Modern Computing Techniques: A Mini-review|
|Keywords:||autonomous;intelligent control system;machine learning;loT;big data|
|Abstract:||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.|
|Appears in Collections:||Dept of Electronic and Computer Engineering Research Papers|
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