人机协同对工业任务感知认知负荷和可用性的影响:一项探索性实验

Étienne Fournier, Dorilys Kilgus, Aurelie Landry, Belal Hmedan, D. Pellier, H. Fiorino, C. Jeoffrion
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引用次数: 8

摘要

职业应用由于cobot(协作机器人)越来越多地被引入工业环境,意识到它们对人类合作者的潜在积极和消极影响至关重要。这项研究通过识别与使用cobot相关的潜在收益(减少感知时间需求、手势数量和错误数量)和担忧(cobot需要很长时间才能感知其环境,这导致完成时间增加)来指导职业卫生工作者。在我们的研究中,组装任务中人类和机器人之间的协作不会对感知认知负荷产生负面影响,增加完成时间(但减少感知时间需求),并减少参与者做出的手势数量和犯下的错误数量。因此,与cobot协作执行任务提高了用户的体验和性能,但完成时间增加了。这项研究为研究如何改进cobot以确保人机系统在工作中的可用性开辟了途径。技术摘要背景工业4.0采用智能技术来提高生产力并降低相关风险。工业界认为,使用cobot是一种潜在的手段,可以减少物理约束并提高性能,而不必取代人为因素。研究尚未证明这些益处对人类有益。目的本研究的目的是确定使用cobot是否改善了操作员的感知认知负荷和系统的可用性。方法参与者使用Duplos复制三个构建模型。大约一半的参与者(n = 32)单独完成任务,而另一半用cobot(n = 22)。然后,我们使用NASA-TLX来测量工作量,并通过子维度来测量感知认知负荷。还测量了完成时间(每个模型)、错误次数(放置和替换工件)和手势次数(上肢运动)。结果与cobot的协作导致手势显著减少(51对74),错误更少(2对8),感知时间需求减少,但完成时间增加(136对55 s) 。感知认知负荷不受cobot的影响(36对37)。结论我们得出结论,与适应人类可变性的cobot合作是可能的,它可以带来更好的性能,并可以提高系统可用性的某些方面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Impacts of Human-Cobot Collaboration on Perceived Cognitive Load and Usability during an Industrial Task: An Exploratory Experiment
OCCUPATIONAL APPLICATIONS Since cobots (collaborative robots) are increasingly being introduced in industrial environments, being aware of their potential positive and negative impacts on human collaborators is essential. This study guides occupational health workers by identifying the potential gains (reduced perceived time demand, number of gestures and number of errors) and concerns (the cobot takes a long time to perceive its environment, which leads to an increased completion time) associated with working with cobots. In our study, the collaboration between human and cobot during an assembly task did not negatively impact perceived cognitive load, increased completion time (but decreased perceived time demand), and decreased the number of gestures performed by participants and the number of errors made. Thus, performing the task in collaboration with a cobot improved the user’s experience and performance, except for completion time, which increased. This study opens avenues to investigate how to improve cobots to ensure the usability of the human-machine system at work. TECHNICAL ABSTRACT Background Industry 4.0 implements smart technologies to increase productivity and to decrease the associated risks. Using cobots is considered by industry as a potential means to reduce physical constraints and improve performance without having to replace the human factor. Research has yet to prove these benefits on humans. Purpose The goal of this study was to determine if working with a cobot improved perceived cognitive load of an operator and the usability of the system. Methods Participants replicated three construction models using Duplos. Approximatively half of our participants (n = 32) accomplished the task alone and the other half accomplished the same task with a cobot (n = 22). We then used the NASA-TLX to measure workload and, through a sub-dimension, perceived cognitive load. Completion time (for each model), number of errors (placing and replacing a piece), and the number of gestures (movements of the upper limbs) were also measured. Results Collaboration with a cobot led to significantly fewer gestures (51 vs. 74), fewer errors (2 vs. 8), and reduced perceived time demand but increased completion time (136 vs. 55 s). Perceived cognitive load was not impacted by the cobot (36 vs. 37). Conclusion We conclude that collaboration with a cobot adapting to human variability is possible, and that it could lead to better performance and could improve certain dimensions of system usability.
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