Industry 5.0 paradigm has renewed interest in the human sphere, emphasizing the importance of workers’ wellbeing in manufacturing activities. In such context, collaborative robotics originated as a technology to support humans in tiring and repetitive tasks. This study investigates the effects of assembly complexity in Human-Robot collaboration using physiological indicators of cognitive effort. In a series of experiments, participants performed assembly processes of different products with varying complexity, in two modalities: manually and with cobot assistance. Physiological measures, including skin conductance, heart rate variability and eye-tracking metrics were collected. The analysis of physiological signals showed trends suggesting the impact of assembly complexity and cobot support. One key finding of the study is that a single physiological signal usually may not provide a complete understanding of cognitive load. Therefore, a holistic approach should be followed. This approach highlighted the importance of considering multiple measures simultaneously to accurately assess workers’ wellbeing in industrial environments.

Assembly complexity and physiological response in human-robot collaboration: Insights from a preliminary experimental analysis / Capponi, Matteo; Gervasi, Riccardo; Mastrogiacomo, Luca; Franceschini, Fiorenzo. - In: ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING. - ISSN 0736-5845. - STAMPA. - 89:(2024), pp. 1-16. [10.1016/j.rcim.2024.102789]

Assembly complexity and physiological response in human-robot collaboration: Insights from a preliminary experimental analysis

Matteo Capponi;Riccardo Gervasi;Luca Mastrogiacomo;Fiorenzo Franceschini
2024

Abstract

Industry 5.0 paradigm has renewed interest in the human sphere, emphasizing the importance of workers’ wellbeing in manufacturing activities. In such context, collaborative robotics originated as a technology to support humans in tiring and repetitive tasks. This study investigates the effects of assembly complexity in Human-Robot collaboration using physiological indicators of cognitive effort. In a series of experiments, participants performed assembly processes of different products with varying complexity, in two modalities: manually and with cobot assistance. Physiological measures, including skin conductance, heart rate variability and eye-tracking metrics were collected. The analysis of physiological signals showed trends suggesting the impact of assembly complexity and cobot support. One key finding of the study is that a single physiological signal usually may not provide a complete understanding of cognitive load. Therefore, a holistic approach should be followed. This approach highlighted the importance of considering multiple measures simultaneously to accurately assess workers’ wellbeing in industrial environments.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2988824