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

Jerry Chen1, Maysam Abbod2, Jiann-Shing Shieh3

  • 1Department of Mechanical engineering, Yuan Ze University, Taoyuan 32003, Taiwan. s1088701@mail.yzu.edu.tw.

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Summary
This summary is machine-generated.

Autonomous systems excel in unknown environments where classical control fails. This paper reviews autonomous systems and their integration with advanced technologies like the Internet of Things and federated learning.

Keywords:
IoTautonomousbig datafederated learningintelligent control systemmachine learning

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Area of Science:

  • Control Systems Engineering
  • Artificial Intelligence
  • Robotics

Background:

  • Classical control systems are limited to static environments and struggle with uncertainty.
  • Autonomous systems, originating from control systems research, are designed for unknown and dynamic environments.
  • The emulation of human behavior for problem-solving is a key interdisciplinary focus.

Purpose of the Study:

  • To provide a comprehensive overview of the state-of-the-art in autonomous systems.
  • To define, model, and describe the structure of autonomous systems.
  • To explore future integration of autonomous systems with emerging technologies.

Main Methods:

  • Literature review and synthesis of current research on autonomous systems.
  • Analysis of the definition, modeling, and system architecture of autonomous agents.
  • Discussion of advanced integration concepts, including Internet of Things (IoT), big data, Over-the-Air (OTA) updates, and federated learning.

Main Results:

  • Autonomous systems offer a robust alternative to classical control in uncertain environments.
  • The paper details the foundational aspects of autonomous system design and operation.
  • Integration pathways with advanced technologies are identified for enhanced capabilities.

Conclusions:

  • Autonomous systems are crucial for problem-solving in unpredictable settings.
  • Future research should focus on integrating autonomous systems with IoT, big data, OTA, and federated learning.
  • The study provides a roadmap for advancing towards full autonomy and beyond.