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    This study introduces an augmented reality (AR) assembly system using hypergraphs and Large Language Models (LLMs) for improved procedural guidance. The novel approach enhances user experience and task efficiency in complex assembly operations.

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    Area of Science:

    • Human-Computer Interaction
    • Manufacturing Technology
    • Artificial Intelligence

    Background:

    • Conventional liaison graphs struggle to represent procedural logic in complex assembly tasks.
    • Visual instructions in augmented reality (AR) can impose a significant cognitive burden on users.
    • Existing AR guidance systems often lack intuitive narration and user-centric design.

    Purpose of the Study:

    • To develop an expressive structure for representing complex assembly tasks in AR.
    • To create a narration workflow using Large Language Models (LLMs) to mediate instruction complexity.
    • To evaluate the effectiveness of the proposed AR assembly guidance system through a user study.

    Main Methods:

    • Utilized an assembly hypergraph to capture hierarchical task information.
    • Employed an A* search algorithm to generate an optimal assembly path.
    • Designed an LLM-mediated narration workflow with an optimizer for fluent and intuitive instruction delivery.

    Main Results:

    • Transitioning from liaison graphs to hypergraphs improved objective outcomes (reduced task time and errors) and subjective ratings.
    • LLM-mediated narration maintained performance gains while lowering cognitive load and enhancing user experience.
    • A within-subjects study (N=24) demonstrated progressive improvements with each component of the proposed method.

    Conclusions:

    • The proposed AR assembly design, integrating hypergraphs and LLM narration, significantly enhances user performance and experience.
    • LLMs can serve as a valuable mediation layer for improving user interaction in AR guidance systems.
    • The findings highlight the potential of advanced computational structures and AI for optimizing complex assembly processes.