AVICol: Adaptive Visual Instruction for Remote Collaboration Using Mixed Reality

Lili Wang, Xiangyu Li, Jian Wu, Dong Zhou, Im Sio Kei, Voicu Popescu

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

This article describes a mixed reality visual instruction approach for remote collaboration between a trainee and an expert. The expert authors the visual instructions through a virtual reality interface. The instructions are shown to the trainee overlaid onto the workspace using an augmented reality interface. The approach achieves effectiveness and efficiency by addressing three challenges. First, the expert-authored visual instructions are shown to the trainee by taking into account occlusions with the 3D workspace; Second, in addition to abstract visual instructions implemented by arrows, the expert can also author highly suggestive instructions by depicting the target state of the workspace realistically by selecting, copying, pasting, and repositioning workspace objects; Third, multiple instructions can be concatenated in sequences that the trainee executes on their own, without any additional guidance from the expert; The approach has been evaluated in a controlled user study with three experiments. The experiment verification confirms that compared to the conventional instruction, this approach achieves significantly lower error rates, shorter task completion times, and lower rotation angular errors. Moreover, the approach allows the trainee to execute the entire sequence robustly, without real-time instruction from the expert.

Original languageEnglish
JournalInternational Journal of Human-Computer Interaction
DOIs
StateAccepted/In press - 2024
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2024 Taylor & Francis Group, LLC.

Keywords

  • asynchronous collaboration
  • augmented reality
  • mixed reality
  • Object manipulation
  • remote collaboration
  • synchronous collaboration
  • trainee expert collaboration
  • virtual reality

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