Towards smarter workplaces: integrating real-time cognitive feedback in collaborative robotics
提出一种动态任务分配系统，根据生产率和瞳孔直径等认知指标实时调整任务，实验表明该方法能提升任务一致性、降低认知负荷并保持生产率，有助于实现工业5.0以人为本的目标。
In recent years, there has been a significant shift towards a more human-centric approach in academic and industrial fields, emphasising the well-being of workers as a central element of production. This transformation, a key pillar of Industry 5.0, advocates for technologies that adapt to workers' needs rather than the other way around. Despite advances in automation, many tasks still require human flexibility, dexterity, and judgment, underscoring the importance of collaborative robotics. These robots combine the efficiency of automated systems with the adaptability of human operators. However, traditional static task allocation methods often fail to balance productivity and cognitive load, resulting in inefficiencies and increased operator strain. This paper introduces a dynamic task allocation system that addresses these gaps by incorporating real-time adjustments based on both productivity metrics and cognitive factors, such as pupil diameter as an indicator of mental stress. An experimental campaign involving 20 participants compared static and dynamic task allocation methods. The results demonstrate that dynamic task assignment significantly improves task performance consistency, reduces cognitive load, and maintains productivity. These findings highlight the necessity of dynamic task assignment in collaborative environments to achieve operational efficiency and enhanced operator well-being, aligning with the human-centric goals of Industry 5.0.