Offloading robot control with 5G
Research output: Contribution to book/conference proceedings/anthology/report › Conference contribution › Contributed
Contributors
Abstract
Simultaneous Localization and Mapping (SLAM), among other critical functions of mobile robots, such as navigation, are computationally expensive. When deployed at the robot, those functions demand high energy consumption and result in shorter operation time. Offloading SLAM to an Edge Cloud (EC) can significantly reduce the robot's computing demand and resources, subsequently reducing energy consumption. We offload intelligence of mobile robot control functionality, i.e., navigation, localization, and control to an EC. The EC processes sensor data and sends the robot the directional velocities. Meanwhile, a 5G wireless connection ensures the necessary low latencies and high throughputs. We demonstrate the feasibility of offloading SLAM and navigation in an EC based on a use case in automotive production. Additionally, we developed a digital twin of the robot and visualized its current sensor data.
Details
Original language | English |
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Title of host publication | 2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC) |
Pages | 461-464 |
Number of pages | 4 |
ISBN (electronic) | 978-1-6654-3161-3 |
Publication status | Published - 10 Jan 2022 |
Peer-reviewed | No |
Publication series
Series | IEEE Consumer Communications and Networking Conference |
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ISSN | 2331-9852 |
External IDs
Scopus | 85135730229 |
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dblp | conf/ccnc/SossallaR0F22 |
ORCID | /0000-0001-7008-1537/work/142248638 |
ORCID | /0000-0001-8469-9573/work/161891022 |