Exploiting visual cues for safe and flexible cyber-physical production systems

Islam, SOB, Lughmani, WA, Qureshi, WS, Khalid, A ORCID logoORCID: https://orcid.org/0000-0001-5270-6599, Mariscal, MA and Garcia-Herrero, S, 2019. Exploiting visual cues for safe and flexible cyber-physical production systems. Advances in Mechanical Engineering, 11 (12). ISSN 1687-8132

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Abstract

Human workers are envisioned to work alongside robots and other intelligent factory modules, and fulfill supervision tasks in future smart factories. Technological developments, during the last few years, in the field of smart factory automation have introduced the concept of cyber-physical systems, which further expanded to cyber-physical production systems. In this context, the role of collaborative robots is significant and depends largely on the advanced capabilities of collision detection, impedance control, and learning new tasks based on artificial intelligence. The system components, collaborative robots, and humans need to communicate for collective decision-making. This requires processing of shared information keeping in consideration the available knowledge, reasoning, and flexible systems that are resilient to the real-time dynamic changes on the industry floor as well as within the communication and computer network infrastructure. This article presents an ontology-based approach to solve industrial scenarios for safety applications in cyber-physical production systems. A case study of an industrial scenario is presented to validate the approach in which visual cues are used to detect and react to dynamic changes in real time. Multiple scenarios are tested for simultaneous detection and prioritization to enhance the learning surface of the intelligent production system with the goal to automate safety-based decisions.

Item Type: Journal article
Publication Title: Advances in Mechanical Engineering
Creators: Islam, S.O.B., Lughmani, W.A., Qureshi, W.S., Khalid, A., Mariscal, M.A. and Garcia-Herrero, S.
Publisher: Sage
Date: December 2019
Volume: 11
Number: 12
ISSN: 1687-8132
Identifiers:
Number
Type
10.1177/1687814019897228
DOI
1263147
Other
Rights: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
Divisions: Schools > School of Science and Technology
Record created by: Jonathan Gallacher
Date Added: 20 Jan 2020 16:57
Last Modified: 20 Jan 2020 16:59
URI: https://irep.ntu.ac.uk/id/eprint/39022

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