自动化学科面临的挑战

孙长银; 吴国政; 王志衡; 丛杨; 穆朝絮; 贺威

doi:10.16383/j.aas.c200904

自动化学科面临的挑战

doi: 10.16383/j.aas.c200904

孙长银^1,,
吴国政^2,,
王志衡^2,,
丛杨^{2, 3,},
穆朝絮^4,,
贺威^5,

1.
东南大学自动化学院南京 210096
2.
国家自然科学基金委员会信息科学部北京 100085
3.
中国科学院沈阳自动化研究所机器人学国家重点实验室沈阳 110016
4.
天津大学电气自动化与信息工程学院天津 300072
5.
北京科技大学自动化学院北京 100083

基金项目: 国家自然科学基金(61942301)资助

详细信息

作者简介:
孙长银：东南大学自动化学院教授. 主要研究方向为智能控制与优化, 强化学习, 神经网络, 数据驱动控制. E-mail: cysun@seu.edu.cn

吴国政：博士, 国家自然科学基金委员会信息科学部三处处长. 主要研究方向为人工智能. 本文通信作者. E-mail: wugz@nsfc.gov.cn

王志衡：博士, 国家自然科学基金委员会信息科学部三处项目主任. 主要研究方向为自动化. E-mail: wangzh@nsfc.gov.cn

丛杨：中国科学院沈阳自动化研究所研究员, 目前为国家自然科学基金委员会信息科学部三处流动项目主任. 主要研究方向为计算机视觉, 智能视频处理, 机器学习, 机器人伺服. E-mail: congyang@nsfc.gov.cn

穆朝絮：天津大学电气自动化与信息工程学院教授. 主要研究方向为强化学习, 自适应学习系统, 智能控制和优化. E-mail: cxmu@tju.edu.cn

贺威：北京科技大学自动化学院教授. 主要研究方向为机器人学, 振动控制和智能控制系统. E-mail: weihe@ieee.org

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出版历程
- 收稿日期: 2020-10-29
- 网络出版日期: 2020-12-18
- 刊出日期: 2021-02-20

On Challenges in Automation Science and Technology

SUN Chang-Yin^1
,,
WU Guo-Zheng^2
,,
WANG Zhi-Heng^2
,,
CONG Yang^{2, 3
,},
MU Chao-Xu^4
,,
HE Wei^5
,

1.
School of Automation, Southeast University, Nanjing 210096
2.
Department of Information Sciences, National Natural Science Foundation of China, Beijing 100085
3.
State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016
4.
School of Electrical and Information Engineering, Tianjin University, Tianjin 300072
5.
School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083

Funds: Supported by National Natural Science Foundation of China (61942301)

More Information

Author Bio:
SUN Chang-Yin　Professor at the School of Automation, Southeast University. His research interest covers intelligent control and optimization, reinforcement learning, neural networks, data-driven control

WU Guo-Zheng　Ph. D., director of Division 3 in the Department of Information Sciences, National Natural Science Foundation of China. His main research interest is artificial intelligence. Corresponding author of this paper

WANG Zhi-Heng　Ph. D., program director of Division 3 in the Department of Information Sciences, National Natural Science Foundation of China. His main research interest is automation

CONG Yang　Professor at the Shenyang Institute of Automation, Chinese Academy of Sciences. He is currently a non-permanent program director in the Department of Information Sciences, National Natural Science Foundation of China. His research interest covers computer vision, intelligent video processing, machine learning, robot servo

MU Chao-Xu　Professor at the School of Electrical and Information Engineering, Tianjin University. Her research interest covers reinforcement learning, adaptive and learning systems, intelligent control and optimization

HE Wei　Professor at the School of Automation and Electrical Engineering, University of Science and Technology Beijing. His research interest covers robotics, vibration control and intelligent control systems

摘要

摘要:
本文分析了控制理论与应用、模式识别与智能系统、导航制导与控制、系统科学与工程、人工智能与自动化交叉等领域的发展现状. 结合科技发展、国内国际研究前沿和新兴领域对自动化科学技术的需求, 提出重点发展智能控制理论和方法、高性能作业机器人、信息物理系统、导航与控制技术、重大装备自动化技术、自主智能系统和人工智能驱动的自动化技术优先领域, 加强数据驱动控制理论、人工智能基础理论研究, 进一步发展人机协同、跨域融合的智能自动化, 为实现国家社会的全面信息化智能化提供理论和技术保障.
- 自动化科学技术 /
- 机器人 /
- 信息物理系统 /
- 导航制导与控制 /
- 装备自动化 /
- 自主智能系统 /
- 人工智能
Abstract:
This paper analyzes the current development of automation science and technology, including fields of control theory and application, pattern recognition and intelligent system, navigation guidance and control, system science and engineering, as well as the interdisciplinary research of artificial intelligence and automation. Combining with the requirements of science and technology development, domestic and international research frontiers, and emerging technologies, the priority areas and specific research directions are put forward to develop intelligent control theory and methodology, high performance robot, cyber-physical system, navigation and control technology, equipment automation technology, autonomous intelligent system and artificial-intelligence-based automation. It is expected to establish the theory framework of data-driven control and artificial-intelligence-based automation. With the intelligent automation of human-machine cooperation and multi-technology integration, it will provide theoretical and technical support for the realization of comprehensive intelligent society.
- Automation science and technology /
- robot /
- cyber-physical system /
- navigation guidance and control /
- equipment automation technology /
- autonomous intelligent system /
- artificial intelligence

HTML全文

图 1 智能控制理论研究方向

Fig. 1 Research directions of intelligent control theory

下载: 全尺寸图片幻灯片

图 2 高性能作业机器人主要发展方向和关键技术

Fig. 2 Development directions and key technologies of high performance robots

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图 3 信息物理系统主要研究方向

Fig. 3 Research directions of cyber-physical systems

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图 4 导航制导与控制领域的重要进展及发展趋势

Fig. 4 Important progress and trend of navigation, guidance and control

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图 5 重大装备智能控制与维护

Fig. 5 Intelligent control and maintenance of automatic equipments

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图 6 自主智能系统的总体发展思路

Fig. 6 Development strategy of autonomous intelligent systems

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图 7 人工智能和自动化交叉领域若干前沿研究方向

Fig. 7 Cutting-edge research directions in automation with AI

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