Augmented Reality Spatial Tracking for Parts Identification
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Solution Overview
Problem
Existing augmented reality (AR) systems lose spatial awareness and rendering capabilities when visible patterns or fiducial markers move out of the user's field of view, requiring reacquisition and leading to inefficiencies in identifying and locating parts needed for tasks.
Innovation Solution
An AR system that tracks and renders parts both within and outside the user's current field of view using a camera, computer vision algorithms, and inertial sensors, maintaining spatial awareness and providing visual cues for part identification and retrieval without the need for reacquisition when parts move in or out of view.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the AR system relies on visible patterns within the current field of view to maintain spatial awareness, then the system can accurately render graphics and identify parts when they are visible, but the system loses spatial awareness and rendering capabilities when patterns move out of the field of view
Solution Approach 1:
The patent extends the tracking capability from the 2D field of view to a 3D field of regard, using depth estimation and spatial modeling to maintain awareness of parts outside the current camera view. This dimensional extension allows the system to track parts in the broader environment beyond what is immediately visible.
Solution Approach 2:
The system performs preliminary tracking and identification of parts before they enter or while they are at the boundaries of the field of view. By maintaining a buffer zone and pre-processing spatial relationships, the system prepares for parts that will soon enter or exit the view, preventing loss of spatial awareness.
2Measurement precision
If the AR system uses a narrow field of view for detailed part identification, then the system can accurately identify parts within view, but the system cannot track parts outside the current view
Solution Approach 1:
The system compensates for the narrow field of view by adding depth perception and spatial modeling capabilities. Through stereo vision, depth from focus, or structure-from-motion techniques, the system builds a 3D understanding of the environment that extends beyond the 2D field of view, enabling tracking of parts in the broader field of regard.
Solution Approach 2:
The patent introduces intermediate spatial models and predictive algorithms that act as mediators between the limited field of view and the broader field of regard. These intermediaries maintain spatial relationships and predict part locations even when parts are not currently visible, bridging the gap between narrow viewing and broad coverage.
3Measurement precision
If the AR system requires reacquisition of parts when they enter or exit the field of view, then the system maintains accuracy for visible parts, but the system experiences delays and inefficiencies in part retrieval tasks
Solution Approach 1:
The system maintains continuous tracking of parts across field of view boundaries by establishing and maintaining spatial models that persist even when parts are not visible. This continuity eliminates the need to restart tracking when parts enter or exit the view, maintaining both accuracy and efficiency throughout the task.
Solution Approach 2:
The system performs preliminary spatial mapping and part tracking in advance, building a comprehensive model of the environment and part locations before tasks begin. This preliminary work enables the system to quickly reference and guide users to parts without requiring reacquisition during the task execution.
Data Source
AI summary
An AR system both identifies and visually tracks parts for a user by maintaining spatial awareness of the user's pose and provides instructions to the user for the use of those parts. Tracking the identified parts, both inside and outside the current Field of View (FOV), and any missing parts for use with the current instruction improves the effectiveness and efficiency of both novice and experienced user alike.