Training-effectiveness of a mixed reality system for human–robot collaboration in industrial settings

IF 5.9
Computers & Education: X Reality Pub Date : 2026-06-01 Epub Date: 2026-01-12 DOI:10.1016/j.cexr.2026.100135
Silvio Lang, Tom Pfister, Tobias Kaupp
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Abstract

The integration of collaborative robots into manufacturing has significantly transformed industry dynamics by enhancing the effectiveness and adaptability of production processes. This study investigates the potential of mixed reality (MR) technology to revolutionize employee training through immersive and interactive environments that seamlessly merge digital and physical realities. We introduce an MR training system for human–robot collaborative assembly tasks and evaluate its effectiveness as a training tool. The evaluation applies the following metrics: User Experience, Interaction Effectiveness, Affective-Cognitive Response, Technology Readiness, and Task Completion Time. Sixty-three participants with varied technical backgrounds, experience levels, and job roles completed a collaborative assembly task using the MR system. Our analysis includes (1) the overall effectiveness of the MR system on an absolute scale, and (2) the difference in effectiveness given the participants’ backgrounds. For the latter, participants were split into two MR-Affinity groups. Our results suggest that the MR system can effectively train people to jointly work with robots. Secondly, no significant difference between the two MR-Affinity groups was found except for the Task Completion Time. Both results together indicate that MR-based training for human–robot collaboration is generally useful and applicable to users from varied backgrounds.
工业环境中人机协作的混合现实系统的训练有效性
协作机器人与制造业的集成通过提高生产过程的有效性和适应性,显著地改变了工业动态。本研究探讨了混合现实(MR)技术的潜力,通过无缝融合数字和物理现实的沉浸式和交互式环境,彻底改变员工培训。我们介绍了一种用于人机协作装配任务的MR训练系统,并评估了它作为一种训练工具的有效性。评估采用以下指标:用户体验、交互效果、情感认知反应、技术准备和任务完成时间。63名具有不同技术背景、经验水平和工作角色的参与者使用MR系统完成了一个协作组装任务。我们的分析包括(1)MR系统在绝对尺度上的整体有效性,以及(2)在参与者背景下的有效性差异。对于后者,参与者被分成两个MR-Affinity组。我们的研究结果表明,MR系统可以有效地训练人与机器人共同工作。其次,除了任务完成时间外,两个MR-Affinity组之间没有发现显著差异。这两个结果共同表明,基于磁共振的人机协作训练通常是有用的,适用于来自不同背景的用户。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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