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Active collision avoidance for human-robot collaboration driven by vision sensors
Department of Production Engineering, KTH Royal Institute of Technology, Stockholm, Sweden.
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och Automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0002-8906-630X
Department of Production Engineering, KTH Royal Institute of Technology, Stockholm, Sweden.
2017 (English)In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 30, no 9, 970-980 p.Article in journal (Refereed) Published
Abstract [en]

Establishing safe human-robot collaboration is an essential factor for improving efficiency and flexibility in today's manufacturing environment. Targeting safety in human-robot collaboration, this paper reports a novel approach for effective online collision avoidance in an augmented environment, where virtual three-dimensional (3D) models of robots and real images of human operators from depth cameras are used for monitoring and collision detection. A prototype system is developed and linked to industrial robot controllers for adaptive robot control, without the need of programming by the operators. The result of collision detection reveals four safety strategies: the system can alert an operator, stop a robot, move away the robot, or modify the robot's trajectory away from an approaching operator. These strategies can be activated based on the operator's existence and location with respect to the robot. The case study of the research further discusses the possibility of implementing the developed method in realistic applications, for example, collaboration between robots and humans in an assembly line.

Place, publisher, year, edition, pages
Taylor & Francis, 2017. Vol. 30, no 9, 970-980 p.
Keyword [en]
collision detection, collaborative assembly, safety, vision sensor
National Category
Robotics
Research subject
Production and Automation Engineering
Identifiers
URN: urn:nbn:se:his:diva-13825DOI: 10.1080/0951192X.2016.1268269ISI: 000402991300006Scopus ID: 2-s2.0-85006100717OAI: oai:DiVA.org:his-13825DiVA: diva2:1113661
Available from: 2017-06-22 Created: 2017-06-22 Last updated: 2017-11-27Bibliographically approved

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Schmidt, Bernard

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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