Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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
Human-machine Collaboration in Virtual Reality for Adaptive Production Engineering
KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).ORCID iD: 0000-0003-4616-189X
KTH, School of Industrial Engineering and Management (ITM), Production Engineering.ORCID iD: 0000-0002-0006-283X
KTH, School of Industrial Engineering and Management (ITM), Production Engineering.ORCID iD: 0000-0001-8679-8049
2017 (English)In: Procedia Manufacturing, ISSN 2351-9789, Vol. 11, p. 1279-1287Article in journal (Refereed) Published
Abstract [en]

This paper outlines the main steps towards an open and adaptive simulation method for human-robot collaboration (HRC) in production engineering supported by virtual reality (VR). The work is based on the latest software developments in the gaming industry, in addition to the already commercially available hardware that is robust and reliable. This allows to overcome VR limitations of the industrial software provided by manufacturing machine producers and it is based on an open-source community programming approach and also leads to significant advantages such as interfacing with the latest developed hardware for realistic user experience in immersive VR, as well as the possibility to share adaptive algorithms. A practical implementation in Unity is provided as a functional prototype for feasibility tests. However, at the time of this paper, no controlled human-subject studies on the implementation have been noted, in fact, this is solely provided to show preliminary proof of concept. Future work will formally address the questions that are raised in this first run.

Place, publisher, year, edition, pages
Elsevier B.V. , 2017. Vol. 11, p. 1279-1287
Keywords [en]
Adaptive Production, Augmented Reality, Human-Robot Collaboration, Industry 4.0, Robotics, Unity Game Engine, Virtual Reality
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
URN: urn:nbn:se:kth:diva-216563DOI: 10.1016/j.promfg.2017.07.255Scopus ID: 2-s2.0-85029856140OAI: oai:DiVA.org:kth-216563DiVA, id: diva2:1155635
Note

QC 20171108

Available from: 2017-11-08 Created: 2017-11-08 Last updated: 2017-11-08Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

de Giorgio, AndreaRomero, MarioOnori, MauroWang, Lihui

Search in DiVA

By author/editor
de Giorgio, AndreaRomero, MarioOnori, MauroWang, Lihui
By organisation
KTHComputational Science and Technology (CST)Production Engineering
Production Engineering, Human Work Science and Ergonomics

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 276 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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