HUMANISE: Human-Inspired Smart Management, towards a Healthy and Safe Industrial Collaborative Robotics
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
Affiliations
Karmele Lopez-de-Ipina
Department of Psychiatry, University of Cambridge, Cambridge CB2 3PT, UK
Jon Iradi
EleKin Lab, Systems Engineering and Automation, Computers’ Architecture and Technology, and Enterprise Management Departments, University of the Basque Country UPV/EHU, 20018 Donostia-San Sebastian, Spain
Elsa Fernandez
EleKin Lab, Systems Engineering and Automation, Computers’ Architecture and Technology, and Enterprise Management Departments, University of the Basque Country UPV/EHU, 20018 Donostia-San Sebastian, Spain
Pilar M. Calvo
EleKin Lab, Systems Engineering and Automation, Computers’ Architecture and Technology, and Enterprise Management Departments, University of the Basque Country UPV/EHU, 20018 Donostia-San Sebastian, Spain
Damien Salle
Tecnalia Research Centre, Tecnalia Industry and Transport Division, 20009 Donostia-San Sebastia, Spain
Anujan Poologaindran
Department of Psychiatry, University of Cambridge, Cambridge CB2 3PT, UK
Ivan Villaverde
Tecnalia Research Centre, Tecnalia Industry and Transport Division, 20009 Donostia-San Sebastia, Spain
Paul Daelman
Tecnalia Research Centre, Tecnalia Industry and Transport Division, 20009 Donostia-San Sebastia, Spain
Emilio Sanchez
Department of Mechanical Engineering and Materials, Engineering School, University of Navarra, TECNUN, 20018 Donostia-San Sebastian, Spain
Catalina Requejo
Cajal Institute, Consejo Superior de Investigaciones Científicas (CSIC), 28002 Madrid, Spain
John Suckling
Department of Psychiatry, University of Cambridge, Cambridge CB2 3PT, UK
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.
