System disruptions
We are currently experiencing disruptions on the search portals due to high traffic. We are working to resolve the issue, you may temporarily encounter an error message.
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Edge connected ARWs
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0001-9685-1026
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0001-8235-2728
2023 (English)In: Aerial Robotic Workers: Design, Modeling, Control, Vision, and Their Applications / [ed] George Nikolakopoulos, Sina Sharif Mansouri, Christoforos Kanellakis, Elsevier, 2023, p. 245-253Chapter in book (Other academic)
Abstract [en]

This chapter focuses on edge computing that is a key technology of industry 4.0 for ARWs and robotic platforms in general. In many missions, ARWs and robots are required to operate autonomously, which commonly means the development of computationally heavy and demanding algorithms. In an effort to expand their capabilities, edge computing has been established as a promising solution. With its utilization, ARWs can take the advantage of edge-significant resources, thus allowing the offloading of the computationally intense processes. Similar to the cloud robotics systems that are associated with high network communication costs, the edge robotics provide minimal latency, since the edge layer is located much closer to the robots. Thus, ARWs can successfully operate in real-time. The integration of edge computing with ARWs and robotic platforms can enable an ecosystem where robots can communicate and collaborate with each other and operators in accomplishing challenging tasks with high performance and in real-time.

Place, publisher, year, edition, pages
Elsevier, 2023. p. 245-253
Keywords [en]
Edge computing, Communication, Virtual machine, Docker
National Category
Robotics and automation Computer Systems
Research subject
Robotics and Artificial Intelligence
Identifiers
URN: urn:nbn:se:ltu:diva-97384DOI: 10.1016/B978-0-12-814909-6.00019-6Scopus ID: 2-s2.0-85150136703ISBN: 978-0-12-814909-6 (print)OAI: oai:DiVA.org:ltu-97384DiVA, id: diva2:1758947
Available from: 2023-05-24 Created: 2023-05-24 Last updated: 2025-02-05Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Seisa, Achilleas SantiKoval, Anton

Search in DiVA

By author/editor
Seisa, Achilleas SantiKoval, Anton
By organisation
Signals and Systems
Robotics and automationComputer Systems

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 113 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf