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地下空间无人系统研究综述

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地下空间作为人类活动空间不可分割的部分,是继宇宙空间、海洋资源外可开拓的第三大领域,也是继陆、海、空、天、电、网之后的第七维战略空间.无人系统通过跨域协同合作可涌现出单个主体难以实现的智能水平,在地下空间发挥关键作用.本文针对地下空间无人系统相关需求,围绕地下空间各领域相关研究进展,梳理其关键技术研究现状及未来发展趋势.介绍了地下矿井无人开采系统、地下轨道交通无人系统、地下管廊综合管理系统、地下空间无人作战系统的国内外研究现状;对地下空间通信、地下空间态势感知、自主导航定位及集群协同控制关键技术进行概述,并指出现存的问题;对地下空间无人系统未来发展趋势进行了展望.
Review of unmanned systems research in underground space
As an integral part of human activity space,underground space is the third largest area that can be developed after cosmic space and ocean resources,as well as the seventh-dimension strategic space after land,sea,air,space,elec-tricity,and network.Unmanned systems play a key role in the underground space by collaborating across domains,and it can emerge with a level of intelligence that is difficult for a single subject to realize.In response to related require-ments of underground space unmanned systems,the current research progress and future development trends of key technologies in various fields of underground space are summarized.First,the research status of domestic and interna-tional unmanned mining systems in underground mines,unmanned systems for underground rail transit,comprehensive management systems for underground pipelines,and unmanned combat systems for underground spaces are introduced.Then,an overview of key technologies of underground communication technology,underground situational awareness technology,autonomous navigation and localization,and swarm collaborative control are summarized,and existing problems are pointed out.Finally,the future development trends of underground unmanned systems are discussed.

underground spaceunmanned systemscross-domain collaborationreliable communicationsituational awarenesscluster collaborationautonomous planningintelligent interaction

王军、王佳慧、李玉莲、陈世海、吴保磊

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中国矿业大学 信息与控制工程学院, 江苏 徐州 221116

地下空间智能控制教育部工程研究中心, 江苏 徐州 221116

江苏省地下空间智能感知与无人系统创新平台, 江苏 徐州 221116

地下空间 无人系统 跨域协同 可靠通信 态势感知 集群协作 自主规划 智能交互

科技部科技创新2030—"新一代人工智能"重大项目中国高校产学研创新基金

2020AAA01073002021ZYA02011

2024

10.11992/tis.202304035

智能系统学报
中国人工智能学会　哈尔滨工程大学

智能系统学报

CSTPCD北大核心
影响因子：0.672
ISSN：1673-4785
年,卷(期)：2024.19(1)
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