Name
Abstract | ||
|---|---|---|
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. (C) 2022 The Authors. Published by Elsevier B.V. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.procs.2022.01.387 | 3RD INTERNATIONAL CONFERENCE ON INDUSTRY 4.0 AND SMART MANUFACTURING |
Keywords | DocType | Volume |
Digital twin, human-robot collaboration, human cyber-physical system, 5G communication network, edge-cloud collaboration | Conference | 200 |
ISSN | Citations | PageRank |
1877-0509 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yanjun Shi | 1 | 0 | 0.34 |
| Weiming Shen | 2 | 0 | 0.34 |
| Lihui Wang | 3 | 0 | 0.34 |
| Francesco Longo | 4 | 0 | 0.68 |
| Letizia Nicoletti | 5 | 0 | 1.01 |
| Antonio Padovano | 6 | 0 | 0.68 |