Evaluating the Advantages of Remote SLAM on an Edge Cloud
Research output: Contribution to book/conference proceedings/anthology/report › Conference contribution › Contributed › peer-review
Contributors
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
Original language | English |
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Title of host publication | 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2021 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 1-4 |
ISBN (electronic) | 978-1-7281-2989-1 |
Publication status | Published - 2021 |
Peer-reviewed | Yes |
Publication series
Series | IEEE International Conference on Emerging Technologies and Factory Automation, ETFA |
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Volume | 2021-September |
ISSN | 1946-0740 |
Conference
Title | 26th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2021 |
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Duration | 7 - 10 September 2021 |
City | Virtual, Vasteras |
Country | Sweden |
External IDs
Scopus | 85122947873 |
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