Building Trust and safety Correlates for Autonomous Systems using Physiological, Behavioral, and Subjective Measures

Z. Zakeri, Azfar Khalid, Ahmet Omurtag, Greg Hilliard, P. Breedon
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引用次数: 1

Abstract

The use of collaborative robots (cobots) in the industrial setting has grown and continues to expand globally, especially in the context of the smart factory. Mistrust and stress results, as cobots don’t provide facial, auditory, and visual cues that workers normally use to predict behavior. For quantification of mental stress, physiological, behavioral and subjective measures are integrated, processed and analyzed in a smart factory lab setting. The impact on the human workers as mental stress and fatigue conditions are correlated with the task complexity, speed of work, length of collaborative task and cobot payload etc. Multimodal functional neuroimaging was used to record participants’ neural and cardiac activity, in addition to the standard subjective and behavioral measures as they collaborated with robots in multitasking contexts. Preliminary results show that task complexity is positively correlated with beta and gamma band power, left prefrontal cortex activation, and heart rate, while it is negatively correlated with alpha band power during task performance.
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使用生理、行为和主观措施建立自主系统的信任和安全关联
协作机器人(cobots)在工业环境中的使用已经增长并继续在全球范围内扩展,特别是在智能工厂的背景下。由于协作机器人不提供员工通常用来预测行为的面部、听觉和视觉线索,因此会导致不信任和压力。为了量化精神压力,在智能工厂实验室环境中整合、处理和分析生理、行为和主观测量。精神压力和疲劳状态对人类工人的影响与任务复杂性、工作速度、协作任务长度和协作机器人载荷等相关。多模态功能神经成像用于记录参与者在多任务环境下与机器人合作时的神经和心脏活动,以及标准的主观和行为测量。初步结果表明,任务复杂性与任务执行过程中β、γ波段功率、左前额叶皮层激活和心率呈正相关,与α波段功率呈负相关。
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