ABSTRACT

The research of augmented reality physical tasks for human-computer collaboration is still an attractive dynamic research field. In recent years, AR Instruction supporting collaborative assembly has been developed, which can transfer graphic annotation between man and machine. However, there is little research on high precision manual assembly. This paper proposes a high-precision cognitive AR representation (M-AR) for manual operation guidance, which aims to transform a high-precision assembly relationship into a series of visual information to meet the user’s cognition of high-precision task intention. Using this representation, we conducted a within-subject case study to compare it with original AR representation (original AR) and low-precision cognitive AR representation. The results showed that there were significant differences in execution time and operation errors. The user’s subjective feedback also showed that M-AR supporting cognitive feedback can significantly improve a user’s cognitive experience in a physical task.

摘要

用于人机协作的增强现实物理任务的研究仍然是一个有吸引力的动态研究领域。近年来开发了支持协同装配的AR指令，可以在人机之间传递图形标注。然而，对于高精度手工装配的研究却很少。本文提出了一种用于人工操作指导的高精度认知AR表示（M-AR），旨在将高精度装配关系转化为一系列视觉信息，以满足用户对高精度任务意图的认知。使用这种表示，我们进行了主体内案例研究，将其与原始 AR 表示（原始 AR）和低精度认知 AR 表示进行比较。结果表明，在执行时间和操作错误方面存在显着差异。用户的主观反馈还表明，支持认知反馈的 M-AR 可以显着提高用户在体力任务中的认知体验。