3D Point Cloud Registration for Survey Data Accuracy
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Solution Overview
Problem
Traditional survey methods require trained professionals and expensive equipment to derive accurate spatial attributes for imaged objects, and involve time-consuming measurements that can take hours or days, with post-processing needed for Earth Centered Earth Fixed measurements.
Innovation Solution
A system utilizing a server to collect and process 3D survey data from sources like LiDAR, RADAR, and image data from user devices, employing techniques like Structure from Motion and Iterative Closest Point to build and fit 3D point clouds, reducing user effort and processing complexity by using known object vertices for registration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional survey methods are used with trained professionals and expensive equipment, then accurate spatial attributes can be derived, but the process is time-consuming and requires post-processing
Solution Approach 1:
The patent creates a 3D point cloud copy of the surveyed area using aerial imagery and LiDAR data, which can be processed and analyzed without requiring physical presence of surveyors. This digital replica allows multiple measurements and analyses to be performed simultaneously, dramatically reducing survey time while maintaining accuracy.
Solution Approach 2:
The system performs preliminary processing of aerial imagery and LiDAR data to pre-generate the 3D point cloud and extract spatial attributes before they are needed. This preliminary action includes automatic feature detection, coordinate system transformation, and measurement calculation, eliminating the need for time-consuming field measurements and post-processing.
2Measurement precision
If traditional survey methods are used, then accurate measurements can be obtained, but expensive equipment and trained professionals are required
Solution Approach 1:
The system uses multi-functional data collection that simultaneously captures both 2D aerial imagery and 3D LiDAR point cloud data using the same aerial platform. This universal approach eliminates the need for separate specialized equipment for different measurement types and can be operated by personnel with basic training rather than requiring highly specialized surveyors.
Solution Approach 2:
The patent replaces traditional mechanical measurement systems (total stations, theodolites, GPS equipment) with automated photogrammetric and LiDAR processing systems. The mechanical field measurement process is substituted with automated image processing algorithms that perform feature detection, matching, and 3D reconstruction, requiring minimal human intervention and specialized equipment.
3Loss of information
If Earth Centered Earth Fixed measurements are taken, then coordinate data is obtained, but post-processing is required to place data into meaningful earth-specific space
Solution Approach 1:
The system introduces an intermediary coordinate transformation process that converts ECEF coordinates to local ground-based coordinate systems using a reference ellipsoid and transformation parameters. This intermediary step automatically handles the complex mathematical transformations, eliminating the need for manual post-processing while preserving all coordinate information and ensuring accurate placement in earth-specific space.
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
Increases survey data accuracy, detects previously undetected data, and allows for higher fidelity and timely change detection in surveyed assets, providing users with greater control over scan frequency and accessibility.
Implementation Method 1
The server may obtain 3D survey data previously gathered utilizing aerial scanning Light Detection And Ranging (LiDAR) techniques
Implementation Method 2
The server may obtain 3D survey data previously gathered utilizing photogrammetric methods or Radio Detection and Ranging (RADAR) techniques
Data Source
AI summary
Various embodiments are directed to deriving spatial attributes for imaged objects utilizing three-dimensional (3D) information. A server may obtain 3D survey data about an object from a pre-existing source. The server may then receive image data describing the object from a user device. The server may then utilize range imagery techniques to build a 3D point cloud from imagery in a pixel space. The server may then utilize horizontal positioning to place the 3D point cloud in proximity to the 3D survey data. The server may then fit the 3D survey data to the 3D point cloud. Finally, the server may record measurements and absolute locations of interest from the 3D point cloud and send them to the user device.