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Cited by 269

The DOI matches its Crossref record; 78 of the 78 references it cites were found in a registry or an index.

A Review of Recent Advances in Automated Guided Vehicle Technologies: Integration Challenges and Research Areas for 5G-Based Smart Manufacturing Applications

Open access
Oyekanlu, Emmanuel A., Smith, Alexander C., Thomas, Windsor P., Mulroy, Grethel, Hitesh, Dave, Ramsey, Matthew, Kuhn, David J., Mcghinnis, Jason D., Buonavita, Steven C., Looper, Nickolus A., Ng, Mason, Ng'oma, Anthony, Liu, Weimin, Mcbride, Patrick G., Shultz, Michael G., Cerasi, Craig, Sun, Dan·2020·IEEE Access
DOI 10.1109/access.2020.3035729
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Abstract

In industrial environments, over several decades, Automated Guided Vehicles (AGVs) and Autonomous Mobile Robots (AMRs) have served to improve efficiencies of intralogistics and material handling tasks. However, for system integrators, the choice and effective deployment of improved, suitable and reliable communication and control technologies for these unmanned vehicles remains a very challenging task. Specifics of communication for AGVs and AMRs imposes stringent performance requirements on latency and reliability of communication links which many existing wireless technologies struggle to satisfy. In this paper, a review of latest AGVs and AMRs research results in the past decade is presented. The review encompasses results from different past and present research domains of AGVs. In addition, performance requirements of communication networks in terms of their latencies and reliabilities when they are deployed for AGVs and AMRs coordination, control and fleet management in smart manufacturing environments are discussed. Integration challenges and limitations of present state-of-the-art AGV and AMR technologies when those technologies are used for facilitating AGV-based smart manufacturing and factory of the future applications are also thoroughly discussed. The paper also present a thorough discussion of areas in need of further research regarding the application of 5G networks for AGVs and AMRs fleet management in smart manufacturing environments. In addition, novel integration ideas by which tactile Internet, 5G network slicing and virtual reality applications can be used to facilitate AGV and AMR based factory of the future (FoF) and smart manufacturing applications were motivated.

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Metadata

Authors
Oyekanlu, E. A., Smith, A. C., Thomas, W. P., Mulroy, G., Hitesh, D., Ramsey, M., Kuhn, D. J., Mcghinnis, J. D., Buonavita, S. C., Looper, N. A., Ng, M., Ng'oma, A., Liu, W., Mcbride, P. G., Shultz, M. G., Cerasi, C., & Sun, D.
Venue
IEEE Access
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2020
Volume
8
Pages
202312-202353
ISSN
2169-3536 (ISSN-L)
DOI
10.1109/access.2020.3035729
OpenAlex
W3096574182
Cited by
269
References
78
FWCI
22.70
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: A Review of Recent Advances in Automated Guided Vehicle Technologies: Integration Challenges and Research Areas for 5G-Based Smart Manufacturing Applications. https://app.cochat.ai/papers/10.1109/access.2020.3035729
The paper
Oyekanlu, E. A., Smith, A. C., Thomas, W. P., Mulroy, G., Hitesh, D., Ramsey, M., Kuhn, D. J., Mcghinnis, J. D., Buonavita, S. C., Looper, N. A., Ng, M., Ng'oma, A., Liu, W., Mcbride, P. G., Shultz, M. G., Cerasi, C., & Sun, D. (2020). A Review of Recent Advances in Automated Guided Vehicle Technologies: Integration Challenges and Research Areas for 5G-Based Smart Manufacturing Applications. IEEE Access. https://doi.org/10.1109/access.2020.3035729

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.