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A human-driven control architecture for promoting good mental health in collaborative robot scenarios

Matteo Lavit Nicora, Elisabeth André, Daniel Berkmans, Claudia Carissoli, Tiziana D’Orazio, Antonella Delle Fave, Patrick Gebhard, Roberto Marani, Robert Mihai Mira, Luca Negri, Fabrizio Nunnari, Alberto Peña Fernández, Alessandro Scano, Gianluigi Reni, Matteo Malosio

Year
2021
Citations
17

Abstract

This paper introduces the control architecture of a platform aimed at promoting good mental health for workers interacting with collaborative robots (cobots). The platform aim is to render industrial production cells capable of automatically adapting their behavior in order to improve the operator’s quality of experience and level of engagement and to minimize his/her psychological strain. In order to achieve such a goal, an extremely rich and complex framework is required. Starting from the identification of the parameters that could influence the collaboration experience, the envisioned human- driven control structure is presented together with a detailed description of the components required to implement such an automated system. Future works will include proper tuning of control parameters with dedicated experimental sessions, together with the definition of organizational and technical guidelines for the design of a mental-health-friendly cobot-based manufacturing workplace.

Keywords

Control (management)ArchitectureComputer scienceQuality (philosophy)RobotHuman–robot interactionIdentification (biology)Process managementHuman–computer interactionOrder (exchange)

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