Information-level AR instruction: a novel assembly guidance information representation assisting user cognition

Zhuo Wang, Xiaoliang Bai, Shusheng Zhang, Weiping He, Xiangyu Zhang, Li Zhang, Peng Wang, Dechuan Han, Yuxiang Yan

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

Recently, there are some problems in AR instruction research in assembly field, such as irregular instruction design form and redundant display of instruction content. The reason is that there is no AR instruction design rule for AR assembly. The goal of this rule should be to maximize users’ cognitive efficiency of guided content. In order to solve this problem, this paper carries out relevant research work. Firstly, the definition of AR instruction at geometric level and information level is given, and the corresponding design rules of AR instruction, namely, geometric level visualization (GLV) and information-level visualization (ILV), are proposed under these two definitions. Then, a data processing model oriented to the above rules is established, and the relationship and difference between them are elaborated. And then, according to GLV and ILV, four visual interfaces are designed to guide AR assembly. A case study was designed to test the performance of the four interfaces under the two specifications in terms of assembly time, operation experience (including enjoyment, concentration, self-confidence, natural intuition, feasibility, effectiveness, availability, and comprehensibility). Finally, through the test results of each interface, the influencing factors of ILV on user’s assembly efficiency, cognitive efficiency, and understanding are determined, and three implications of ILV are summarized. The results show that ILV with MBD design elements can improve user’s operating experience better than GLV.

Original languageEnglish
Pages (from-to)603-626
Number of pages24
JournalInternational Journal of Advanced Manufacturing Technology
Volume106
Issue number1-2
DOIs
StatePublished - 1 Jan 2020

Keywords

  • Assembly
  • Augmented reality
  • Precision
  • User cognition
  • Visualization

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