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Novel Robotic Arm Working-Area AI Protection System

From traditionally handmade items to the ability of people to use machines to process and even to human-robot collaboration, there are many risks. Traditional manual lathes and milling machines, sophisticated robotic arms, and computer numerical control (CNC) operations are quite dangerous. To ensur...

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Detalles Bibliográficos
Autores principales: Lee, Jeng-Dao, Jheng, En-Shuo, Kuo, Chia-Chen, Chen, Hong-Ming, Hung, Ying-Hsiu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10007316/
https://www.ncbi.nlm.nih.gov/pubmed/36904969
http://dx.doi.org/10.3390/s23052765
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author Lee, Jeng-Dao
Jheng, En-Shuo
Kuo, Chia-Chen
Chen, Hong-Ming
Hung, Ying-Hsiu
author_facet Lee, Jeng-Dao
Jheng, En-Shuo
Kuo, Chia-Chen
Chen, Hong-Ming
Hung, Ying-Hsiu
author_sort Lee, Jeng-Dao
collection PubMed
description From traditionally handmade items to the ability of people to use machines to process and even to human-robot collaboration, there are many risks. Traditional manual lathes and milling machines, sophisticated robotic arms, and computer numerical control (CNC) operations are quite dangerous. To ensure the safety of workers in automated factories, a novel and efficient warning-range algorithm is proposed to determine whether a person is in the warning range, introducing YOLOv4 tiny-object detection algorithms to improve the accuracy of determining objects. The results are displayed on a stack light and sent through an M-JPEG streaming server so that the detected image can be displayed through the browser. According to the experimental results of this system installed on a robotic arm workstation, it is proved that it can ensure recognition reaches 97%. When a person enters the dangerous range of the working robotic arm, the arm can be stopped within about 50 ms, which will effectively improve the safety of its use.
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spelling pubmed-100073162023-03-12 Novel Robotic Arm Working-Area AI Protection System Lee, Jeng-Dao Jheng, En-Shuo Kuo, Chia-Chen Chen, Hong-Ming Hung, Ying-Hsiu Sensors (Basel) Article From traditionally handmade items to the ability of people to use machines to process and even to human-robot collaboration, there are many risks. Traditional manual lathes and milling machines, sophisticated robotic arms, and computer numerical control (CNC) operations are quite dangerous. To ensure the safety of workers in automated factories, a novel and efficient warning-range algorithm is proposed to determine whether a person is in the warning range, introducing YOLOv4 tiny-object detection algorithms to improve the accuracy of determining objects. The results are displayed on a stack light and sent through an M-JPEG streaming server so that the detected image can be displayed through the browser. According to the experimental results of this system installed on a robotic arm workstation, it is proved that it can ensure recognition reaches 97%. When a person enters the dangerous range of the working robotic arm, the arm can be stopped within about 50 ms, which will effectively improve the safety of its use. MDPI 2023-03-02 /pmc/articles/PMC10007316/ /pubmed/36904969 http://dx.doi.org/10.3390/s23052765 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lee, Jeng-Dao
Jheng, En-Shuo
Kuo, Chia-Chen
Chen, Hong-Ming
Hung, Ying-Hsiu
Novel Robotic Arm Working-Area AI Protection System
title Novel Robotic Arm Working-Area AI Protection System
title_full Novel Robotic Arm Working-Area AI Protection System
title_fullStr Novel Robotic Arm Working-Area AI Protection System
title_full_unstemmed Novel Robotic Arm Working-Area AI Protection System
title_short Novel Robotic Arm Working-Area AI Protection System
title_sort novel robotic arm working-area ai protection system
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10007316/
https://www.ncbi.nlm.nih.gov/pubmed/36904969
http://dx.doi.org/10.3390/s23052765
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