Please use this identifier to cite or link to this item:
https://doi.org/10.21256/zhaw-20791
Publication type: | Article in scientific journal |
Type of review: | Peer review (publication) |
Title: | A mixed-perception approach for safe human–robot collaboration in industrial automation |
Authors: | Mohammadi Amin, Fatemeh Rezayati, Maryam van de Venn, Hans Wernher Karimpour, Hossein |
et. al: | No |
DOI: | 10.3390/s20216347 10.21256/zhaw-20791 |
Published in: | Sensors |
Volume(Issue): | 20 |
Issue: | 21 |
Page(s): | 6347 |
Issue Date: | 2020 |
Publisher / Ed. Institution: | MDPI |
ISSN: | 1424-8220 |
Language: | English |
Subjects: | Safe physical human–robot collaboration; Collision detection; Human action recognition; Artificial intelligence; Industrial automation |
Subject (DDC): | 006: Special computer methods 621.3: Electrical, communications, control engineering |
Abstract: | Digital-enabled manufacturing systems require a high level of automation for fast and low-cost production but should also present flexibility and adaptiveness to varying and dynamic conditions in their environment, including the presence of human beings; however, this presence of workers in the shared workspace with robots decreases the productivity, as the robot is not aware about the human position and intention, which leads to concerns about human safety. This issue is addressed in this work by designing a reliable safety monitoring system for collaborative robots (cobots). The main idea here is to significantly enhance safety using a combination of recognition of human actions using visual perception and at the same time interpreting physical human–robot contact by tactile perception. Two datasets containing contact and vision data are collected by using different volunteers. The action recognition system classifies human actions using the skeleton representation of the latter when entering the shared workspace and the contact detection system distinguishes between intentional and incidental interactions if physical contact between human and cobot takes place. Two different deep learning networks are used for human action recognition and contact detection, which in combination, are expected to lead to the enhancement of human safety and an increase in the level of cobot perception about human intentions. The results show a promising path for future AI-driven solutions in safe and productive human–robot collaboration (HRC) in industrial automation. |
URI: | https://digitalcollection.zhaw.ch/handle/11475/20791 |
Fulltext version: | Published version |
License (according to publishing contract): | CC BY 4.0: Attribution 4.0 International |
Departement: | School of Engineering |
Organisational Unit: | Institute of Mechatronic Systems (IMS) |
Appears in collections: | Publikationen School of Engineering |
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2020_Mohammadi-Amin-etal_Safe-human-robot-collaboration-in-industrial-automation.pdf | 2.93 MB | Adobe PDF | View/Open |
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Mohammadi Amin, F., Rezayati, M., van de Venn, H. W., & Karimpour, H. (2020). A mixed-perception approach for safe human–robot collaboration in industrial automation. Sensors, 20(21), 6347. https://doi.org/10.3390/s20216347
Mohammadi Amin, F. et al. (2020) ‘A mixed-perception approach for safe human–robot collaboration in industrial automation’, Sensors, 20(21), p. 6347. Available at: https://doi.org/10.3390/s20216347.
F. Mohammadi Amin, M. Rezayati, H. W. van de Venn, and H. Karimpour, “A mixed-perception approach for safe human–robot collaboration in industrial automation,” Sensors, vol. 20, no. 21, p. 6347, 2020, doi: 10.3390/s20216347.
MOHAMMADI AMIN, Fatemeh, Maryam REZAYATI, Hans Wernher VAN DE VENN und Hossein KARIMPOUR, 2020. A mixed-perception approach for safe human–robot collaboration in industrial automation. Sensors. 2020. Bd. 20, Nr. 21, S. 6347. DOI 10.3390/s20216347
Mohammadi Amin, Fatemeh, Maryam Rezayati, Hans Wernher van de Venn, and Hossein Karimpour. 2020. “A Mixed-Perception Approach for Safe Human–Robot Collaboration in Industrial Automation.” Sensors 20 (21): 6347. https://doi.org/10.3390/s20216347.
Mohammadi Amin, Fatemeh, et al. “A Mixed-Perception Approach for Safe Human–Robot Collaboration in Industrial Automation.” Sensors, vol. 20, no. 21, 2020, p. 6347, https://doi.org/10.3390/s20216347.
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