Evaluating the Advantages of Remote SLAM on an Edge Cloud
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Beitragende
Abstract
The Simultaneous Localization and Mapping (SLAM) method is becoming more and more established for the localization of mobile robots in indoor environments. Due to the high complexity of SLAM, high computing resources are necessary, which leads to a shorter runtime. By using edge computing and higher bandwidths of new wireless technologies, the computing can be outsourced. In this work, the SLAM process is offloaded from a mobile robot to an edge cloud and the impact of more computing power is investigated. We show that outsourcing has performance advantages in terms of the update rate of the map generation as well as the localization.
Details
Originalsprache | Englisch |
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Titel | 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2021 |
Herausgeber (Verlag) | Institute of Electrical and Electronics Engineers Inc. |
Seiten | 1-4 |
ISBN (elektronisch) | 978-1-7281-2989-1 |
Publikationsstatus | Veröffentlicht - 2021 |
Peer-Review-Status | Ja |
Publikationsreihe
Reihe | IEEE International Conference on Emerging Technologies and Factory Automation, ETFA |
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Band | 2021-September |
ISSN | 1946-0740 |
Konferenz
Titel | 26th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2021 |
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Dauer | 7 - 10 September 2021 |
Stadt | Virtual, Vasteras |
Land | Schweden |
Externe IDs
Scopus | 85122947873 |
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