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Human motion prediction for human-robot collaboration
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
2017 (English)In: Journal of manufacturing systems, ISSN 0278-6125, E-ISSN 1878-6642, Vol. 44, p. 287-294Article in journal (Refereed) Published
Abstract [en]

In human-robot collaborative manufacturing, industrial robots would work alongside human workers who jointly perform the assigned tasks seamlessly. A human-robot collaborative manufacturing system is more customised and flexible than conventional manufacturing systems. In the area of assembly, a practical human-robot collaborative assembly system should be able to predict a human worker's intention and assist human during assembly operations. In response to the requirement, this research proposes a new human-robot collaborative system design. The primary focus of the paper is to model product assembly tasks as a sequence of human motions. Existing human motion recognition techniques are applied to recognise the human motions. Hidden Markov model is used in the motion sequence to generate a motion transition probability matrix. Based on the result, human motion prediction becomes possible. The predicted human motions are evaluated and applied in task-level human-robot collaborative assembly.

Place, publisher, year, edition, pages
ELSEVIER SCI LTD , 2017. Vol. 44, p. 287-294
Keywords [en]
Human-robot collaboration, Human motion prediction, Assembly
National Category
Materials Engineering
Identifiers
URN: urn:nbn:se:kth:diva-215844DOI: 10.1016/j.jmsy.2017.04.009ISI: 000411772300004Scopus ID: 2-s2.0-85018894393OAI: oai:DiVA.org:kth-215844DiVA, id: diva2:1149794
Conference
45th SME North American Manufacturing Research Conference (NAMRC), JUN 04-08, 2017, Univ So Calif, Los Angeles, CA
Note

QC 20171017

Available from: 2017-10-17 Created: 2017-10-17 Last updated: 2017-10-19Bibliographically approved

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Wang, Lihui

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CiteExportLink to record
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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