Towards a 5G Mobile Edge Cloud Planner for Autonomous Mobile Robots

Taus Mortensen Raunholt; Ignacio Rodriguez; Preben E. Mogensen; Morten Larsen

doi:10.1109/VTC2021-Fall52928.2021.9625208

Towards a 5G Mobile Edge Cloud Planner for Autonomous Mobile Robots

Taus Mortensen Raunholt, Ignacio Rodriguez, Preben E. Mogensen, Morten Larsen

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

8 Citationer (Scopus)

188 Downloads (Pure)

Abstract

As the use of robots increases in industrial environments, there is a need for enhanced centralized cloud management to improve coordination and planning capabilities. This paper explores the suitability of different 5G schemes for migrating robot intelligence to the cloud by communicating the I/O systems of an AMR with a cloud path planner. The paper includes the analysis of the TCP-based I/O-planner communication and puts it in perspective of 5G mobile edge cloud technology. The observed Mbit/s throughput and statistical uplink/downlink splits of the communication indicate that 5G is a suitable technology to reliably operate the planner. This was further validated by 5G emulation, performing a navigation test and a docking station tests, where the cloud-based system operated over the different 5G configurations achieved a performance and accuracy similar to that from the original on-board local planner.

Originalsprog	Engelsk
Titel	IEEE 94th Vehicular Technology Conference (VTC2021-Fall)
Antal sider	5
Forlag	IEEE
Publikationsdato	sep. 2021
Artikelnummer	9625208
ISBN (Trykt)	978-1-6654-1369-5
ISBN (Elektronisk)	978-1-6654-1368-8
DOI	https://doi.org/10.1109/VTC2021-Fall52928.2021.9625208
Status	Udgivet - sep. 2021
Begivenhed	IEEE 94th Vehicular Technology Conference: VTC2021-Fall - Online Varighed: 27 sep. 2021 → 30 sep. 2021 https://events.vtsociety.org/vtc2021-fall/

Konference

Konference	IEEE 94th Vehicular Technology Conference: VTC2021-Fall
Lokation	Online
Periode	27/09/2021 → 30/09/2021
Internetadresse	https://events.vtsociety.org/vtc2021-fall/

Navn	IEEE Vehicular Technology Conference. Proceedings
ISSN	1090-3038

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10.1109/VTC2021-Fall52928.2021.9625208

MiR_cloud_plannerAccepteret manuskript, 2,1 MB

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Citationsformater

@inproceedings{60b5757c2de545fea9687969688fe063,

title = "Towards a 5G Mobile Edge Cloud Planner for Autonomous Mobile Robots",

abstract = "As the use of robots increases in industrial environments, there is a need for enhanced centralized cloud management to improve coordination and planning capabilities. This paper explores the suitability of different 5G schemes for migrating robot intelligence to the cloud by communicating the I/O systems of an AMR with a cloud path planner. The paper includes the analysis of the TCP-based I/O-planner communication and puts it in perspective of 5G mobile edge cloud technology. The observed Mbit/s throughput and statistical uplink/downlink splits of the communication indicate that 5G is a suitable technology to reliably operate the planner. This was further validated by 5G emulation, performing a navigation test and a docking station tests, where the cloud-based system operated over the different 5G configurations achieved a performance and accuracy similar to that from the original on-board local planner.",

keywords = "5G, Autonomous Mobile Robots, Industry 4.0, Industrial IoT, Mobile Edge Computing, Path Planner, Performance Evaluation, Functional Test",

author = "Raunholt, {Taus Mortensen} and Ignacio Rodriguez and {E. Mogensen}, Preben and Morten Larsen",

year = "2021",

month = sep,

doi = "10.1109/VTC2021-Fall52928.2021.9625208",

language = "English",

isbn = "978-1-6654-1369-5",

series = "IEEE Vehicular Technology Conference. Proceedings",

publisher = "IEEE",

booktitle = "IEEE 94th Vehicular Technology Conference (VTC2021-Fall)",

address = "United States",

note = "IEEE 94th Vehicular Technology Conference: VTC2021-Fall ; Conference date: 27-09-2021 Through 30-09-2021",

url = "https://events.vtsociety.org/vtc2021-fall/",

}

Raunholt, TM, Rodriguez, I, E. Mogensen, P & Larsen, M 2021, Towards a 5G Mobile Edge Cloud Planner for Autonomous Mobile Robots. i IEEE 94th Vehicular Technology Conference (VTC2021-Fall)., 9625208, IEEE, IEEE Vehicular Technology Conference. Proceedings, IEEE 94th Vehicular Technology Conference: VTC2021-Fall, 27/09/2021. https://doi.org/10.1109/VTC2021-Fall52928.2021.9625208

Towards a 5G Mobile Edge Cloud Planner for Autonomous Mobile Robots. / Raunholt, Taus Mortensen; Rodriguez, Ignacio; E. Mogensen, Preben et al.
IEEE 94th Vehicular Technology Conference (VTC2021-Fall). IEEE, 2021. 9625208 (IEEE Vehicular Technology Conference. Proceedings).

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

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AU - Raunholt, Taus Mortensen

AU - Rodriguez, Ignacio

AU - E. Mogensen, Preben

AU - Larsen, Morten

PY - 2021/9

Y1 - 2021/9

N2 - As the use of robots increases in industrial environments, there is a need for enhanced centralized cloud management to improve coordination and planning capabilities. This paper explores the suitability of different 5G schemes for migrating robot intelligence to the cloud by communicating the I/O systems of an AMR with a cloud path planner. The paper includes the analysis of the TCP-based I/O-planner communication and puts it in perspective of 5G mobile edge cloud technology. The observed Mbit/s throughput and statistical uplink/downlink splits of the communication indicate that 5G is a suitable technology to reliably operate the planner. This was further validated by 5G emulation, performing a navigation test and a docking station tests, where the cloud-based system operated over the different 5G configurations achieved a performance and accuracy similar to that from the original on-board local planner.

AB - As the use of robots increases in industrial environments, there is a need for enhanced centralized cloud management to improve coordination and planning capabilities. This paper explores the suitability of different 5G schemes for migrating robot intelligence to the cloud by communicating the I/O systems of an AMR with a cloud path planner. The paper includes the analysis of the TCP-based I/O-planner communication and puts it in perspective of 5G mobile edge cloud technology. The observed Mbit/s throughput and statistical uplink/downlink splits of the communication indicate that 5G is a suitable technology to reliably operate the planner. This was further validated by 5G emulation, performing a navigation test and a docking station tests, where the cloud-based system operated over the different 5G configurations achieved a performance and accuracy similar to that from the original on-board local planner.

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KW - Industrial IoT

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KW - Functional Test

U2 - 10.1109/VTC2021-Fall52928.2021.9625208

DO - 10.1109/VTC2021-Fall52928.2021.9625208

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BT - IEEE 94th Vehicular Technology Conference (VTC2021-Fall)

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ER -

Towards a 5G Mobile Edge Cloud Planner for Autonomous Mobile Robots

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