3D Scanning System Using Satellite Positioning for Large Object Registration
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Solution Overview
Problem
Current methods for creating accurate three-dimensional electronic representations of large objects, such as office complexes or shopping malls, face challenges including insufficient visual details, high costs, and difficulties in installing and maintaining reference points, leading to inefficient and inaccurate scanning processes.
Innovation Solution
A scanning system that aligns multiple scans using satellite-based positioning and error correction, combining geometric and color point data to generate accurate, texturized three-dimensional models by synchronizing point and color scanners, and registering scans through appropriate rotations and translations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional laser scanning techniques are used, then geometric shapes can be generated, but reference points must be manually installed on large objects which is difficult and time-consuming
Solution Approach 1:
The patent removes the requirement for physical reference points (targets) from the scanning process. Instead of installing targets on objects, the system uses the object's own geometric features and edges as automatic reference markers, eliminating the manual installation step entirely while maintaining positioning accuracy
Solution Approach 2:
The scanning system automatically identifies and uses the scanned object's own structural features (edges, corners, geometric patterns) as reference points for alignment, rather than requiring external reference targets. The object essentially scans itself to provide alignment information
2Manufacturing precision
If multiple scans are manually combined, then three-dimensional representations can be created, but the process is time-consuming and labor-intensive
Solution Approach 1:
The patent replaces manual visual inspection and manual alignment processes with automated computer-based registration algorithms. The system automatically matches geometric features across multiple scans using computational methods, eliminating manual labor while improving consistency and reducing time
Solution Approach 2:
The system transforms the manual alignment process into an automated parameter optimization problem, where registration algorithms automatically adjust transformation parameters (rotation, translation, scaling) to best align multiple scans based on matched geometric features
3Loss of information
If digital cameras are used for scanning, then visual details can be captured, but manual combination of multiple images is required which reduces efficiency
Solution Approach 1:
The patent merges multiple scanned images and point cloud data into a single integrated three-dimensional representation through automated registration. The system combines geometric data from laser scanning with visual information from digital cameras, merging both data types into a unified model that preserves visual details while improving processing efficiency
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach simplifies scan data processing, enhances accuracy, and reduces costs by providing detailed, texturized three-dimensional models that can be efficiently combined into a single electronic representation, improving the visualization of large objects in navigational maps.
Implementation Method 1
Coordinates of the scanning samples may be determined with a satellite based positioning system
Implementation Method 2
In some laser techniques, a laser beam is reflected off an object to measure distances
Data Source
AI summary
A scanning system scans a surface of a three-dimensional object from a first position and a second position. Using common alignment at these positions, a first scanning sample and a second scanning sample are generated. The first and second scanning samples include point clouds having data points representing positions of the scanned surfaces. The first scanning sample and the second scanning sample are oriented relative to each other based on the common alignment of the scan positions.