无人系统免疫智能技术

doi:10.7527/S1000-6893.2020.24618

观点

本期目录 | 过刊浏览 | 高级检索

前一篇 | 后一篇

无人系统免疫智能技术

郭雷^1,2, 袁源³, 乔建忠¹, 余翔¹

1. 北京航空航天大学自动化科学与电气工程学院, 北京 100083;
2. 北京航空航天大学大数据精准医疗高精尖创新中心, 北京 100083;
3. 西北工业大学航天学院, 西安 710072

收稿日期:2020-08-09 修回日期:2020-08-15 出版日期:2020-11-15 发布日期:2020-08-17
通讯作者: 袁源 E-mail:yuanyuan86@nwpu.edu.cn

Immune intelligence of unmanned system

GUO Lei^1,2, YUAN Yuan³, QIAO Jianzhong¹, YU Xiang¹

1. School of Automation Science and Electrical Engineering, Beihang University, Beijing 100083, China;
2. Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing 100083, China;
3. School of Astronautics, Northwestern Polytechnical University, Xi'an 710072, China

Received:2020-08-09 Revised:2020-08-15 Online:2020-11-15 Published:2020-08-17

摘要/Abstract

摘要： 传统的无人系统人工智能技术重点研究人脑思维、感知和肌电反应等领域的科学发现和技术实现。免疫反应是生物体在面临病毒、细菌和天敌时保持生存和健康的独特生理机制，是智能系统技术研究领域的崭新视点。受动物应对病毒侵袭、环境剧变、天敌威胁等不利态势的免疫反应、保护自我和进化机制启发，提出无人系统在包含攻击、干扰、拒止、封锁、损伤、故障和博弈等恶劣环境和对抗模式下的生存安全问题，建立无人系统免疫智能技术的一般框架，架设无人系统和生物体之间免疫机制的桥梁。主要内容包括无人系统免疫智能技术的基本概念、反应机理、关键技术和研究框架，并分别从感知与诊断、适应与激励、学习与进化等技术层面进行了问题描述。最后，对免疫智能技术的未来研究方向和应用领域进行了展望。

关键词: 免疫机制, 无人系统, 免疫智能, 自愈控制, 免疫控制, 自身耐受性

Abstract: The traditional artificial intelligence of the unmanned system puts research focus on scientific discovery and technical implementation in the fields of human thought, perception and electromyographic response. The immune reaction is a unique physiological mechanism such that the organism could retain survival and health facing with the virus, germ and natural enemy. The so-called immune reaction inspires the unmanned system community, which includes the reaction including coping with the virus invading, the abrupt change of the environment, and the threatening of the natural enemy. In this paper, the survival problems of the unmanned system in the face of the attack, disturbance, jamming, blockade, damage, failure, and gaming are investigated. An universal framework of the immune intelligence of the unmanned system is established. In addition, the gap between the organism and the unmanned system is bridged. Considering the basic concept, reaction mechanism, key techniques and general framework, our paper puts research attention on the unmanned system. The problem is addressed from the perspectives of the perception and diagnosis, adaption and inspiration as well as learning and evolution. Finally, several possible future research directions of the immune intelligence techniques are provided.

Key words: Immune mechanism, unmanned system, immune intelligence, self-healing control, immune control, self-tolerance

中图分类号:

V219

郭雷, 袁源, 乔建忠, 余翔. 无人系统免疫智能技术[J]. 航空学报, 2020, 41(11): 24618-024618.

GUO Lei, YUAN Yuan, QIAO Jianzhong, YU Xiang. Immune intelligence of unmanned system[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020, 41(11): 24618-024618.

参考文献 16

[1]	YANG G Z, BELLINGHAM J, DUPONT P E, et al. The grand challenges of science robotics[J]. Science Robotics, 2018, 3:eaar7650.
[2]	MAZZOLAI B, LASCHI C. A vision for future bioinspired and biohybrid robots[J]. Science Robotics, 2020, 5:eaba6893.
[3]	TRIMMER B A. Metal or muscle? The future of biologically inspired robots[J]. Science Robotics, 2020, 5:eaba6149.
[4]	MARIA A, ALI R. Towards the development of robot immune system:A combined approach involving innate immune cells and T-lymphocytes[J]. Biosystems, 2018, 172, 52-67.
[5]	HU Y, LUO W. Robotic immune systems:An architecture[C]//IEEE Symposium Series on Computational Intelligence (SSCI). Piscataway:IEEE Press, 2018:1098-1103.
[6]	杨照华,祁振强,房建成.空中目标的免疫识别算法[J].光学精密工程,2006,14(5):922-928. YAGN Z Y,QI Z Q,FANG J C.Immune recognition algorithm and its application to air target detection and recognition[J].Optics and Precision Engineering,2006,14(5):922-928(in Chinese).
[7]	GUO L, CAO S. Anti-disturbance control for systems with multiple disturbances[M]. Boca Raton:CRC Press, 2013. [194. GUO L,YU Z,ZHANG X,et al.Safety control system technologies for UAVs:Review and prospect[J].Science in China (Information Sciences), 2020, 50(2):184-194(in Chinese).
[9]	YU X, ZHANG Y M. Sense and avoid technologies with applications to unmanned aircraft systems:Review and prospects[J]. Progress in Aerospace Sciences, 2015, 74:152-166.
[10]	YUAN Y, YANG H, GUO L, et al. Attack analysis and design of networked control systems under attack[M].Boca Raton:CRC Press, 2019.
[11]	BAYAR N, DARMOUL S, HAJRI-GABOUJ S, et al. Fault detection, diagnosis and recovery using artificial immune systems:A review[J]. Engineering Applications of Artificial Intelligence, 2015, 46:43-57.
[12]	CASTRO L N D, ZUBEN F J V. An evolutionary immune network for data clustering[C]//Brazilian Symposium on Neural Networks. Piscataway:IEEE Press, 2000.
[13]	DASGUPTA D, YU S, NINO F. Recent advances in artificial immune systems:Models and applications[J]. Applied Soft Computing, 2011, 11(2):1574-1587.
[14]	CANHAM R, JACKSON A H, TYRRELL A. Robot error detection using an artificial immune system[C]//Conference on Evolvable Hardware. Piscataway:IEEE Press, 2003:199-207.
[15]	焦李成,杜海峰,刘芳,等.免疫优化计算学习与识别[M].北京:科学出版社,2006. JIAO L C,DU H F,LIU F,et al.Immune computation for optimization learning and recognition[J].Beijing:Science Press,2006(in Chinese).
[16]	MASUTTI T A S, CASTRO L N D. A self-organizing neural network using ideas from the immune system to solve the traveling salesman problem[J]. Information Sciences, 2009, 179(10):1454-1468

E-mail：hkxb@buaa.edu.cn

关于我们

期刊社服务

专业学科

封面文章

友情链接

主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

无人系统免疫智能技术

Immune intelligence of unmanned system

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献 16

相关文章 2

编辑推荐

Metrics

本文评价

[1]	王伟, 王钦钊, 刘钢锋, 程慧, 陶溢, 郭傲兵. 地面无人系统反制关键技术分析与综述[J]. 航空学报, 2022, 43(7): 25489-025489.
[2]	郭雷, 朱玉凯, 乔建忠, 郭康, 包为民. 无人系统生存智能与安全、免疫、绿色控制技术[J]. 航空学报, 2022, 43(10): 527129-527129.