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Human-machine Collaboration in Virtual Reality for Adaptive Production Engineering
KTH.
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: 27th International Conference on Flexible Automation and Intelligent Manufacturing, Elsevier, 2017, Vol. 11, p. 1279-1287Conference paper, Published paper (Refereed)
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, 2017. Vol. 11, p. 1279-1287
Series
Procedia Manufacturing
Keyword [en]
Virtual Reality, Augmented Reality, Unity Game Engine, Human-Robot Collaboration, Industry 4.0, Robotics, Adaptive Production
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-218772DOI: 10.1016/j.promfg.2017.07.255Scopus ID: 2-s2.0-85029856140OAI: oai:DiVA.org:kth-218772DiVA, id: diva2:1161495
Conference
FAIM2017, 27-30 June 2017, Modena, Italy
Note

QC 20171211

Available from: 2017-11-30 Created: 2017-11-30 Last updated: 2017-12-11Bibliographically approved

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No full text in DiVA

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Publisher's full textScopushttps://doi.org/10.1016/j.promfg.2017.07.255

Authority records BETA

Romero, MarioOnori, MauroWang, Lihui

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