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IET Cyber-Systems and Robotics
IET Cyber-Systems and Robotics  2021, Vol. 3 Issue (4): 279-280    DOI: https://doi.org/10.1049/csy2.12038
    
Guest Editorial: Autonomous systems: Navigation, learning, and control
Guest Editorial: Autonomous systems: Navigation, learning, and control
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摘要： This is the IET Cyber-systems and Robotics special issue of Autonomous systems: Navigation, learning, and control. Autonomous systems, as very important representatives of Artificial Intelligence technologies, combine mechanical and electronic hardware, operating system, low-level dynamic control, and high-level intelligent decision components to address challenges that demand high-level autonomy and machine intelligence. Autonomous systems such as aerial robotics, ground vehicles, unmanned surface vehicles, and even all-terrain vehicles for aerospace applications, etc., have played an essential role in many aspects. For example, during the COVID-19 pandemic, autonomous systems have been used for disinfection and food delivery to reduce infection risks. However, navigation, learning, and control are critical for realizing true autonomy, which are still left for research. Navigation is a critical technology that works as the high-level intelligent decision component and directly determines the efficiency of conducting autonomous tasks. Learning, which is regarded as the most representative technology of artificial intelligence, has become a dominating method in many fields, such as image processing and understanding. There are also trends of adopting learning-based methods on autonomous robots, which are the perfect field to adopt state-of-the-art artificial intelligence technologies. The low-level dynamic control part, which builds the foundation of autonomous tasks, receives long-term research interest from modern control theory to intelligent control theory.
Abstract: This is the IET Cyber-systems and Robotics special issue of Autonomous systems: Navigation, learning, and control. Autonomous systems, as very important representatives of Artificial Intelligence technologies, combine mechanical and electronic hardware, operating system, low-level dynamic control, and high-level intelligent decision components to address challenges that demand high-level autonomy and machine intelligence. Autonomous systems such as aerial robotics, ground vehicles, unmanned surface vehicles, and even all-terrain vehicles for aerospace applications, etc., have played an essential role in many aspects. For example, during the COVID-19 pandemic, autonomous systems have been used for disinfection and food delivery to reduce infection risks. However, navigation, learning, and control are critical for realizing true autonomy, which are still left for research. Navigation is a critical technology that works as the high-level intelligent decision component and directly determines the efficiency of conducting autonomous tasks. Learning, which is regarded as the most representative technology of artificial intelligence, has become a dominating method in many fields, such as image processing and understanding. There are also trends of adopting learning-based methods on autonomous robots, which are the perfect field to adopt state-of-the-art artificial intelligence technologies. The low-level dynamic control part, which builds the foundation of autonomous tasks, receives long-term research interest from modern control theory to intelligent control theory.
出版日期: 2021-12-19
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Yu Zhang
Fei Gao
Yuxiang Sun
Naira Hovakimyan
Zheng Fang

引用本文:

Yu Zhang, Fei Gao, Yuxiang Sun, Naira Hovakimyan, Zheng Fang. Guest Editorial: Autonomous systems: Navigation, learning, and control. IET Cyber-Systems and Robotics, 2021, 3(4): 279-280.

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https://www.zjujournals.com/iet-csr/CN/https://doi.org/10.1049/csy2.12038    或    https://www.zjujournals.com/iet-csr/CN/Y2021/V3/I4/279

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