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    Area of Science:

    • Computer Vision
    • Robotics
    • Augmented Reality

    Background:

    • Real-time localization and robustness are key challenges in multi-user mobile AR.
    • Lightweight devices require collaborative information to improve tracking accuracy and system resilience.

    Purpose of the Study:

    • To propose a robust centralized collaborative multi-agent VI-SLAM system for mobile AR.
    • To enable efficient, consistent server-side mapping and real-time tracking on mobile devices.

    Main Methods:

    • A lightweight Visual-Inertial Odometry (VIO) frontend on mobile devices for tracking.
    • A remote server backend for updating multiple submaps and performing submap fusion.
    • A map registration and fusion strategy based on covisibility areas for online consistency.

    Main Results:

    • The system achieves globally consistent mapping through submap fusion in overlapping areas.
    • Frontend tracking accuracy is improved by updating the global map to the local map.
    • Tightly coupled strategy ensures consistency of multi-agent frontend pose estimation.

    Conclusions:

    • The proposed VI-SLAM system effectively enhances localization accuracy and robustness in multi-user mobile AR.
    • The system demonstrates efficient server-side mapping and scalable deployment for AR applications.