組立作業における認知負荷をオンライン評価するフレームワーク
An Online Framework for Cognitive Load Assessment in Assembly Tasks
ステレオカメラ画像から頭部姿勢と骨格を追跡し、作業者の注意や不意の動きを解析することで、製造現場でリアルタイムに認知負荷を推定する手法を提案した。
著者: Marta Lagomarsino, Marta Lorenzini, Elena De Momi, Arash Ajoudani
分類: cs.RO, cs.HC
原文アブストラクト
The ongoing trend towards Industry 4.0 has revolutionised ordinary workplaces, profoundly changing the role played by humans in the production chain. Research on ergonomics in industrial settings mainly focuses on reducing the operator's physical fatigue and discomfort to improve throughput and avoid safety hazards. However, as the production complexity increases, the cognitive resources demand and mental workload could compromise the operator's performance and the efficiency of the shop floor workplace. State-of-the-art methods in cognitive science work offline and/or involve bulky equipment hardly deployable in industrial settings. This paper presents a novel method for online assessment of cognitive load in manufacturing, primarily assembly, by detecting patterns in human motion directly from the input images of a stereo camera. Head pose estimation and skeleton tracking are exploited to investigate the workers' attention and assess hyperactivity and unforeseen movements. Pilot experiments suggest that our factor assessment tool provides significant insights into workers' mental workload, even confirmed by correlations with physiological and performance measurements. According to data gathered in this study, a vision-based cognitive load assessment has the potential to be integrated into the development of mechatronic systems for improving cognitive ergonomics in manufacturing.
