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Parallel End-to-End Autonomous Mining: An IoT-Oriented Approach

文献类型：期刊论文

作者Gao, Yu6; Ai, Yunfeng1; Tian, Bin2; Chen, Long3; Wang, Jian4; Cao, Dongpu5; Wang, Fei-Yue2
刊名IEEE INTERNET OF THINGS JOURNAL
出版日期2020-02-01
卷号7期号:2页码:1011-1023
关键词Data mining Transportation Internet of Things Mining equipment Safety Decision making Artificial societies (A) for modeling computational experiments (C) for analysis and parallel execution (P) for control (ACP) approach autonomous truck decision making Internet of Things (IoT) management and control parallel mines
ISSN号2327-4662
DOI10.1109/JIOT.2019.2948470
通讯作者Wang, Fei-Yue(feiyue.wang@ia.ac.cn)
英文摘要This article proposes a new solution for end-to-end autonomous mining operations: Internet of Things (IoT)-based parallel mining, consisting of the concept definition, the solution given, and the concrete realization. The proposed parallel mining is inspired by the artificial societies (A) for modeling, computational experiments (C) for analysis, and parallel execution (P) for control (ACP) approach. The basic framework of parallel mining is given and its advantages are expounded. Then, the solution of parallel mining is proposed, which is mainly composed of four parts: 1) the management and control center for autonomous mining; 2) the autonomous transportation platform of truck; 3) the semiautonomous mining/shovel platform; and 4) the remote takeover platform. Key technologies of IoT-based parallel mining are discussed in detail, namely, network communication, virtual parallel mining construction, mining environment perception over-the-horizon for the moving area and obstacle detection, collaborative decision making, planning, and control for unmanned mining equipment, and parallel taking-over and remote control. Finally, the performance of IoT-based parallel mining, including fusion perception, collaborative decision making, planning, and control, is evaluated. The realization of parallel mining can fundamentally improve the safety of personnel and equipment, reduce the cost of mining operation, and increase the production rate.
WOS关键词CONTROL-SYSTEM
资助项目National Natural Science Foundation of China[61533019] ; National Natural Science Foundation of China[91720000] ; Beijing Municipal Science and Technology Commission[Z181100008918007] ; Intel Collaborative Research Institute for Intelligent and Automated Connected Vehicles
WOS研究方向Computer Science ; Engineering ; Telecommunications
语种英语
WOS记录号WOS:000521981800017
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构National Natural Science Foundation of China ; Beijing Municipal Science and Technology Commission ; Intel Collaborative Research Institute for Intelligent and Automated Connected Vehicles
源URL[http://ir.ia.ac.cn/handle/173211/38779]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队
通讯作者Wang, Fei-Yue
作者单位1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
3.Sun Yat Sen Univ, Sch Data & Comp Sci, Guangzhou, Peoples R China
4.Jilin Univ, Coll Comp Sci & Technol, Changchun, Peoples R China
5.Univ Waterloo, Dept Mech & Mechatron Engn, Waterloo, ON N2L 3G1, Canada
6.Vehicle Intelligence Pioneers Inc, Qingdao 266109, Peoples R China
推荐引用方式
GB/T 7714		 Gao, Yu,Ai, Yunfeng,Tian, Bin,et al. Parallel End-to-End Autonomous Mining: An IoT-Oriented Approach[J]. IEEE INTERNET OF THINGS JOURNAL,2020,7(2):1011-1023.
APA Gao, Yu.,Ai, Yunfeng.,Tian, Bin.,Chen, Long.,Wang, Jian.,...&Wang, Fei-Yue.(2020).Parallel End-to-End Autonomous Mining: An IoT-Oriented Approach.IEEE INTERNET OF THINGS JOURNAL,7(2),1011-1023.
MLA Gao, Yu,et al."Parallel End-to-End Autonomous Mining: An IoT-Oriented Approach".IEEE INTERNET OF THINGS JOURNAL 7.2(2020):1011-1023.

入库方式： OAI收割

来源：自动化研究所

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