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...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/3/1170 |
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| author | Karmele Lopez-de-Ipina Jon Iradi Elsa Fernandez Pilar M. Calvo Damien Salle Anujan Poologaindran Ivan Villaverde Paul Daelman Emilio Sanchez Catalina Requejo John Suckling |
| author_facet | Karmele Lopez-de-Ipina Jon Iradi Elsa Fernandez Pilar M. Calvo Damien Salle Anujan Poologaindran Ivan Villaverde Paul Daelman Emilio Sanchez Catalina Requejo John Suckling |
| author_sort | Karmele Lopez-de-Ipina |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-11T09:26:08Z |
| format | Article |
| id | doaj.art-72d7f7eb56914105a149a4c359363152 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T09:26:08Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-72d7f7eb56914105a149a4c3593631522023-11-16T17:57:09ZengMDPI AGSensors1424-82202023-01-01233117010.3390/s23031170HUMANISE: Human-Inspired Smart Management, towards a Healthy and Safe Industrial Collaborative RoboticsKarmele Lopez-de-Ipina0Jon Iradi1Elsa Fernandez2Pilar M. Calvo3Damien Salle4Anujan Poologaindran5Ivan Villaverde6Paul Daelman7Emilio Sanchez8Catalina Requejo9John Suckling10Department of Psychiatry, University of Cambridge, Cambridge CB2 3PT, UKEleKin Lab, Systems Engineering and Automation, Computers’ Architecture and Technology, and Enterprise Management Departments, University of the Basque Country UPV/EHU, 20018 Donostia-San Sebastian, SpainEleKin Lab, Systems Engineering and Automation, Computers’ Architecture and Technology, and Enterprise Management Departments, University of the Basque Country UPV/EHU, 20018 Donostia-San Sebastian, SpainEleKin Lab, Systems Engineering and Automation, Computers’ Architecture and Technology, and Enterprise Management Departments, University of the Basque Country UPV/EHU, 20018 Donostia-San Sebastian, SpainTecnalia Research Centre, Tecnalia Industry and Transport Division, 20009 Donostia-San Sebastia, SpainDepartment of Psychiatry, University of Cambridge, Cambridge CB2 3PT, UKTecnalia Research Centre, Tecnalia Industry and Transport Division, 20009 Donostia-San Sebastia, SpainTecnalia Research Centre, Tecnalia Industry and Transport Division, 20009 Donostia-San Sebastia, SpainDepartment of Mechanical Engineering and Materials, Engineering School, University of Navarra, TECNUN, 20018 Donostia-San Sebastian, SpainCajal Institute, Consejo Superior de Investigaciones Científicas (CSIC), 28002 Madrid, SpainDepartment of Psychiatry, University of Cambridge, Cambridge CB2 3PT, UKThe 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.https://www.mdpi.com/1424-8220/23/3/1170CobotMachine Learningrisk managementhuman/robot behaviourageing populationworkers’ diseases |
| spellingShingle | Karmele Lopez-de-Ipina Jon Iradi Elsa Fernandez Pilar M. Calvo Damien Salle Anujan Poologaindran Ivan Villaverde Paul Daelman Emilio Sanchez Catalina Requejo John Suckling HUMANISE: Human-Inspired Smart Management, towards a Healthy and Safe Industrial Collaborative Robotics Sensors Cobot Machine Learning risk management human/robot behaviour ageing population workers’ diseases |
| 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 | Cobot Machine Learning risk management human/robot behaviour ageing population workers’ diseases |
| url | https://www.mdpi.com/1424-8220/23/3/1170 |
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