Offloading robot control with 5G

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragen

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

OriginalspracheEnglisch
Titel2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC)
Seiten461-464
Seitenumfang4
ISBN (elektronisch)978-1-6654-3161-3
PublikationsstatusVeröffentlicht - 10 Jan. 2022
Peer-Review-StatusNein

Publikationsreihe

ReiheIEEE Consumer Communications and Networking Conference
ISSN2331-9852

Externe IDs

Scopus 85135730229
dblp conf/ccnc/SossallaR0F22
ORCID /0000-0001-7008-1537/work/142248638
ORCID /0000-0001-8469-9573/work/161891022