Augmented Reality Modeling for Large-Object Display Accuracy
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Solution Overview
Problem
Existing augmented reality systems face challenges in accurately displaying information on large physical objects due to the need for numerous anchors and increased resource consumption, especially when the distance from the device increases, leading to reduced accuracy and higher processing demands.
Innovation Solution
An augmented reality system utilizing a group of unmanned vehicles to generate images and scan data, which are used by a computer system to create an enhanced 3D model with increased detail in specific regions, allowing a portable computing device to accurately display information using simultaneous localization and mapping processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If the distance of the augmented reality device from the anchor increases, then the coverage area increases, but the accuracy of displaying augmented reality information decreases
Solution Approach 1:
The system divides the large physical object into multiple regions, each with its own set of anchors. The portable computing device displays information for a first region when close to it, and can switch to display information for a second region when moved closer to that region. This segmentation allows high accuracy within each local region while covering a large overall area through multiple regions.
Solution Approach 2:
The system transitions from a single global coordinate system to multiple local coordinate systems, each centered on a specific region of interest. This dimensional reorganization allows the system to maintain high precision in each local frame of reference while collectively covering extensive areas through the aggregation of multiple regions.
2Area of stationary object
If the size of the physical object increases, then the coverage area increases, but the number of anchors needed increases beyond feasibility
Solution Approach 1:
The system segments the large physical object into multiple manageable regions, with each region having a limited set of anchors. This segmentation reduces the number of anchors needed in each local region to a feasible amount, while the collective coverage of all regions spans the entire large object.
Solution Approach 2:
Each region is equipped with the appropriate number of anchors needed for that specific local area, rather than uniformly distributing anchors across the entire large object. This local optimization ensures that each region has sufficient anchors for accurate tracking without requiring an excessive total number of anchors for the whole object.
3Measurement precision
If the number of anchors increases to maintain accuracy on large objects, then the display accuracy improves, but the processing resources required increase
Solution Approach 1:
The system processes anchors in segmented groups corresponding to different regions rather than processing all anchors globally. When the device is near a particular region, only the anchors for that region are actively processed for tracking and display, reducing the computational burden while maintaining accuracy for the current region of interest.
4Manufacturing precision
If extensive scanning of the entire object is performed, then the model detail improves, but the processing time and resources increase
Solution Approach 1:
The system creates 3D models segmented by region rather than modeling the entire object at full detail. High-detail models are generated only for regions that are currently being viewed or are of particular interest, while other regions may have lower detail or be generated on-demand. This selective modeling dramatically reduces processing time and resources while maintaining model detail for the active region.
Solution Approach 2:
The system performs scanning and modeling only for the necessary portions of the object at any given time rather than completing exhaustive scanning of the entire object. This partial action approach generates sufficient model detail for current display needs without the excessive time and resource investment required for complete object scanning.
Data Source
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AI summary
A method, apparatus, and system for visualizing information. An augmented reality system comprises a computer system and a visualizer in the computer system. The computer system is in communication with unmanned vehicles using communications links. The visualizer system receives images of a physical object from the unmanned vehicles moving relative to the physical object and receive scan data for a region of the physical object from the unmanned vehicles. The visualizer creates an enhanced model of the physical object using the images and the scan data. The region of the physical object in the enhanced model has a greater amount of detail than the other regions of the physical object. The visualizer sends information to a portable computing device that is displayable by the portable computing device on a live view of the physical object. The information is identified using the enhanced model of the physical object.