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

被引:2
|
作者
Lopez-de-Ipina, Karmele [1 ,2 ,3 ]
Iradi, Jon [2 ,3 ]
Fernandez, Elsa [2 ,3 ]
Calvo, Pilar M. [2 ,3 ]
Salle, Damien [4 ]
Poologaindran, Anujan [1 ,5 ]
Villaverde, Ivan [4 ]
Daelman, Paul [4 ]
Sanchez, Emilio [6 ,7 ]
Requejo, Catalina [8 ]
Suckling, John [1 ]
机构
[1] Univ Cambridge, Dept Psychiat, Cambridge CB2 3PT, England
[2] Univ Basque Country UPV, EleKin Lab Syst Engn & Automation Comp Architectur, San Sebastian 20018, Spain
[3] Univ Basque Country UPV EHU, Enterprise Management Dept, Donostia San Sebastian 20018, Spain
[4] Tecnalia Res Ctr, Tecnalia Ind & Transport Div, Donostia San Sebastia 20009, Spain
[5] Alan Turing Inst, British Lib, London NW1 2DB, England
[6] Univ Navarra, Engn Sch, Dept Mech Engn & Mat, TECNUN, Donostia San Sebastian 20018, Spain
[7] CEIT, Mfg Div, Donostia San Sebastian 20018, Spain
[8] CSIC, Cajal Inst, Madrid 28002, Spain
关键词
Cobot; Machine Learning; risk management; human; robot behaviour; ageing population; workers' diseases; industrial health and safety; RECOGNITION;
D O I
10.3390/s23031170
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
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.
引用
收藏
页数:18
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