Closing the Last Meter: A Markerless AR Framework for Precise Indoor Navigation

Abstract: Indoor navigation remains challenging due to the degradation of Global Positioning System (GPS) signals in enclosed environments, leading to the last-meter problem—the difficulty of guiding users from a building entrance to a precise indoor destination. This challenge is particularly significant for individuals with visual impairments or reduced spatial orientation capabilities navigating complex multi-floor buildings. This paper presents a markerless augmented reality (AR) indoor navigation framework based on visual–inertial SLAM for infrastructure-free localization. The system performs real-time pose estimation on commodity mobile devices, constructs persistent spatial anchors, and computes vector-based navigation paths rendered as dynamically aligned AR overlays. Operating solely on onboard sensing, the framework enables scalable deployment without environmental instrumentation. Experimental evaluation in a two-floor academic building demonstrates centimeter-level localization accuracy for short-range navigation and stable performance across extended trajectories, including staircase transitions. The results support the feasibility of markerless AR navigation as a foundation for precise and accessible last-meter indoor guidance.

Keywords: Augmented Reality, Indoor Navigation, Visual–Inertial SLAM, Markerless Localization, Accessibility, Infrastructure-Free Localization

DOI: 10.54941/ahfe1007198

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