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
Classification, personalised safety framework and strategy for human-robot collaboration
KTH, School of Industrial Engineering and Management (ITM), Production Engineering.ORCID iD: 0000-0001-9694-0483
KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
KTH, School of Industrial Engineering and Management (ITM), Production Engineering.ORCID iD: 0000-0001-8679-8049
2018 (English)In: Proceedings of International Conference on Computers and Industrial Engineering, CIE, Curran Associates Inc. , 2018Conference paper, Published paper (Refereed)
Abstract [en]

The modern manufacturing system calls for a safe, efficient and user-friendly working environment to meet the expectation of Industry 4.0 and Smart Manufacturing. The Human-Robot Collaboration is considered as one of the promising approaches and it attracts major research interest in both academia and industry. However, in the past years the reported research results focus more on the advanced robot controlling methods, while the uniqueness of each individual human is not included in the planning or control loop. In this research, multiple types of relationships between the human operator and robot are first classified into four major types. Then the safety framework and strategy is developed towards a personalised solution in a Human-Robot Collaboration cell. The proposed approach is then implemented and evaluated through case studies and quantifiable result comparisons.

Place, publisher, year, edition, pages
Curran Associates Inc. , 2018.
Keywords [en]
HRC classification, Human-robot collaboration, Safety strategy, Manufacture, Robot programming, Safety engineering, Controlling methods, Research interests, Research results, Result comparison, Smart manufacturing, Working environment, Robots
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-247233Scopus ID: 2-s2.0-85061345176OAI: oai:DiVA.org:kth-247233DiVA, id: diva2:1301614
Conference
48th International Conference on Computers and Industrial Engineering, CIE 2018, 2 December 2018 through 5 December 2018
Note

QC 20190402

Available from: 2019-04-02 Created: 2019-04-02 Last updated: 2019-04-02Bibliographically approved

Open Access in DiVA

No full text in DiVA

Scopus

Authority records BETA

Wang, Xi VincentWang, Lihui

Search in DiVA

By author/editor
Wang, Xi VincentSeira, A.Wang, Lihui
By organisation
Production Engineering
Computer and Information Sciences

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 42 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