A Cognitive Digital Twins Framework for Human-Robot Collaboration Show others and affiliations
2022 (English) In: 3Rd International Conference On Industry 4.0 And Smart Manufacturing / [ed] Longo, F Affenzeller, M Padovano, A, Elsevier BV , 2022, Vol. 200, p. 1867-1874Conference paper, Published paper (Refereed)
Abstract [en]
This paper proposes a cognitive digital twin framework for smart manufacturing, and especially for human-robot-collaboration cases. The proposed framework comprises three layers (field, edge, and cloud layers) based on the 5G communication network. In the field layer, the physical twin's data from the physical machine and human operators are transmitted through the edge layer and then to the cloud layer to virtualize the digital twin. The cloud layer generates inference model generation by deep learning training and updates the inference model in the edge layer to make the field's machine smart. Especially, human operators' models are built based on the multimodal fusion in the cloud layer for cognitive function. Also, edge-cloud collaborative computing is presented to implement the proposed framework. Finally, the study is validated with a human-robot-collaboration case involving 5G edge computing.
Place, publisher, year, edition, pages Elsevier BV , 2022. Vol. 200, p. 1867-1874
Series
Procedia Computer Science, ISSN 1877-0509
Keywords [en]
Digital twin, human-robot collaboration, human cyber-physical system, 5G communication network, edge-cloud collaboration
National Category
Computer Systems Computer Sciences Communication Systems
Identifiers URN: urn:nbn:se:kth:diva-312223 DOI: 10.1016/j.procs.2022.01.387 ISI: 000777601300190 Scopus ID: 2-s2.0-85127779613 OAI: oai:DiVA.org:kth-312223 DiVA, id: diva2:1658273
Conference 3rd International Conference on Industry 4.0 and Smart Manufacturing (ISM), NOV 17-19, 2021, Upper Austria Univ Appl Sci, Hagenberg Campus, Linz, AUSTRIA
Note QC 20220516
2022-05-162022-05-162022-06-25 Bibliographically approved