4.7 Article

Wireless Networked Multirobot Systems in Smart Factories

期刊

PROCEEDINGS OF THE IEEE
卷 109, 期 4, 页码 468-494

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JPROC.2020.3033753

关键词

Smart manufacturing; 5G mobile communication; Robots; Wireless communication; Wireless sensor networks; Production facilities; Robot sensing systems; Fourth Industrial Revolution; 6G mobile communication; Internet of Things; Low latency communication; 5G; 6G; artificial intelligence (AI); cyber– physical system (CPS); cybersecurity; Industry 4; 0; Internet of Things; machine learning; multiagent system; multirobot systems (MRSs); smart factory; smart manufacturing; ultrareliable and low-latency communication (uRLLC); wireless communications; wireless networks

资金

  1. Cyber Florida
  2. North Carolina Department of Transportation (NCDOT) [TCE2020-03]
  3. NC State 2019 Faculty Research and Professional Development Program
  4. Cisco Systems, Inc.
  5. National Science Foundation [CNS-2006453]
  6. Mississippi State University [ORED 253551-060702]
  7. National Science Foundation (NSF)
  8. National Institute of Standards and Technology (NIST)

向作者/读者索取更多资源

Smart manufacturing based on AI and ICT will be a major driver of the digital economy in the coming decades. To achieve flexible production, it is essential to holistically integrate wireless networking, computing, and automatic control technologies. This article discusses the challenges of this complex system engineering from a wireless networking perspective.
Smart manufacturing based on artificial intelligence and information communication technology will become the main contributor to the digital economy of the upcoming decades. In order to execute flexible production, smart manufacturing must holistically integrate wireless networking, computing, and automatic control technologies. This article discusses the challenges of this complex system engineering from a wireless networking perspective. Starting from enabling flexible reconfiguration of a smart factory, we discuss existing wireless technology and the trends of wireless networking evolution to facilitate multirobot smart factories. Furthermore, the special sequential decision-making of a multirobot manufacturing system is examined. Social learning can be used to extend the resilience of precision operation in a multirobot system by taking network topology into consideration, which also introduces a new vision for the cybersecurity of smart factories. A summary of highlights of technological opportunities for holistic facilitation of wireless networked multirobot smart factories rounds off this article.

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