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HUMANISE: Human-Inspired Smart Management, towards a Healthy and Safe Industrial Collaborative Robotics

The workplace is evolving towards scenarios where humans are acquiring a more active and dynamic role alongside increasingly intelligent machines. Moreover, the active population is ageing and consequently emerging risks could appear due to health disorders of workers, which requires intelligent int...

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Autores principales: Lopez-de-Ipina, Karmele, Iradi, Jon, Fernandez, Elsa, Calvo, Pilar M., Salle, Damien, Poologaindran, Anujan, Villaverde, Ivan, Daelman, Paul, Sanchez, Emilio, Requejo, Catalina, Suckling, John
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9920065/
https://www.ncbi.nlm.nih.gov/pubmed/36772209
http://dx.doi.org/10.3390/s23031170
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author Lopez-de-Ipina, Karmele
Iradi, Jon
Fernandez, Elsa
Calvo, Pilar M.
Salle, Damien
Poologaindran, Anujan
Villaverde, Ivan
Daelman, Paul
Sanchez, Emilio
Requejo, Catalina
Suckling, John
author_facet Lopez-de-Ipina, Karmele
Iradi, Jon
Fernandez, Elsa
Calvo, Pilar M.
Salle, Damien
Poologaindran, Anujan
Villaverde, Ivan
Daelman, Paul
Sanchez, Emilio
Requejo, Catalina
Suckling, John
author_sort Lopez-de-Ipina, Karmele
collection PubMed
description The workplace is evolving towards scenarios where humans are acquiring a more active and dynamic role alongside increasingly intelligent machines. Moreover, the active population is ageing and consequently emerging risks could appear due to health disorders of workers, which requires intelligent intervention both for production management and workers’ support. In this sense, the innovative and smart systems oriented towards monitoring and regulating workers’ well-being will become essential. This work presents HUMANISE, a novel proposal of an intelligent system for risk management, oriented to workers suffering from disease conditions. The developed support system is based on Computer Vision, Machine Learning and Intelligent Agents. Results: The system was applied to a two-arm Cobot scenario during a Learning from Demonstration task for collaborative parts transportation, where risk management is critical. In this environment with a worker suffering from a mental disorder, safety is successfully controlled by means of human/robot coordination, and risk levels are managed through the integration of human/robot behaviour models and worker’s models based on the workplace model of the World Health Organization. The results show a promising real-time support tool to coordinate and monitoring these scenarios by integrating workers’ health information towards a successful risk management strategy for safe industrial Cobot environments.
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spelling pubmed-99200652023-02-12 HUMANISE: Human-Inspired Smart Management, towards a Healthy and Safe Industrial Collaborative Robotics Lopez-de-Ipina, Karmele Iradi, Jon Fernandez, Elsa Calvo, Pilar M. Salle, Damien Poologaindran, Anujan Villaverde, Ivan Daelman, Paul Sanchez, Emilio Requejo, Catalina Suckling, John Sensors (Basel) Article The workplace is evolving towards scenarios where humans are acquiring a more active and dynamic role alongside increasingly intelligent machines. Moreover, the active population is ageing and consequently emerging risks could appear due to health disorders of workers, which requires intelligent intervention both for production management and workers’ support. In this sense, the innovative and smart systems oriented towards monitoring and regulating workers’ well-being will become essential. This work presents HUMANISE, a novel proposal of an intelligent system for risk management, oriented to workers suffering from disease conditions. The developed support system is based on Computer Vision, Machine Learning and Intelligent Agents. Results: The system was applied to a two-arm Cobot scenario during a Learning from Demonstration task for collaborative parts transportation, where risk management is critical. In this environment with a worker suffering from a mental disorder, safety is successfully controlled by means of human/robot coordination, and risk levels are managed through the integration of human/robot behaviour models and worker’s models based on the workplace model of the World Health Organization. The results show a promising real-time support tool to coordinate and monitoring these scenarios by integrating workers’ health information towards a successful risk management strategy for safe industrial Cobot environments. MDPI 2023-01-19 /pmc/articles/PMC9920065/ /pubmed/36772209 http://dx.doi.org/10.3390/s23031170 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
Lopez-de-Ipina, Karmele
Iradi, Jon
Fernandez, Elsa
Calvo, Pilar M.
Salle, Damien
Poologaindran, Anujan
Villaverde, Ivan
Daelman, Paul
Sanchez, Emilio
Requejo, Catalina
Suckling, John
HUMANISE: Human-Inspired Smart Management, towards a Healthy and Safe Industrial Collaborative Robotics
title HUMANISE: Human-Inspired Smart Management, towards a Healthy and Safe Industrial Collaborative Robotics
title_full HUMANISE: Human-Inspired Smart Management, towards a Healthy and Safe Industrial Collaborative Robotics
title_fullStr HUMANISE: Human-Inspired Smart Management, towards a Healthy and Safe Industrial Collaborative Robotics
title_full_unstemmed HUMANISE: Human-Inspired Smart Management, towards a Healthy and Safe Industrial Collaborative Robotics
title_short HUMANISE: Human-Inspired Smart Management, towards a Healthy and Safe Industrial Collaborative Robotics
title_sort humanise: human-inspired smart management, towards a healthy and safe industrial collaborative robotics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9920065/
https://www.ncbi.nlm.nih.gov/pubmed/36772209
http://dx.doi.org/10.3390/s23031170
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