3D Laser Scan Registration via Contour Matching
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Solution Overview
Problem
The existing methods for registering multiple laser scans from different viewpoints into a common coordinate system are complex and require precise manual placement of targets, leading to inaccurate positioning and increased complexity.
Innovation Solution
A method and device for simplifying the evaluation of laser scans by relative positioning of scan positions and contours, allowing for easy linking and automatic registration without the need for manual target placement, using a 3D laser scanner with an evaluation unit that enables manual or automatic pre-positioning and fine adjustment, and utilizing sensors like GPS or MEMS for precise positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple laser scans are taken from different points of view and registered into a common coordinate system using conventional methods, then the 3D measurement accuracy is improved, but the complexity of the evaluation process increases significantly due to manual target placement and measurement
Solution Approach 1:
The system automatically identifies and matches characteristic contours across different laser scans without requiring manual target placement. The evaluation unit autonomously performs the registration process by comparing geometric features, eliminating the need for operators to manually measure and record target positions with a total station.
Solution Approach 2:
The patent replaces the manual mechanical measurement process (using total station to measure targets) with an automated computational approach. The evaluation unit uses algorithmic contour matching and coordinate transformation to achieve registration, substituting manual mechanical operations with automated information processing.
2Measurement precision
If manual target placement and measurement is used for registration, then the positioning accuracy can be maintained, but the time required for evaluation increases significantly
Solution Approach 1:
The system pre-identifies characteristic contours in each laser scan before the registration process. These contours serve as pre-prepared reference features that enable rapid automatic matching during registration, eliminating the need for time-consuming manual target measurement while maintaining transformation accuracy.
Solution Approach 2:
The evaluation unit automatically performs the entire registration process including contour matching, coordinate transformation calculation, and application of transformations to point clouds, significantly reducing evaluation time compared to manual methods.
3Ease of operation
If automatic registration methods are used without manual targets, then the evaluation process is simplified, but the measurement precision may be compromised
Solution Approach 1:
The system transforms the registration problem from relying on manually placed targets to utilizing automatically extracted geometric parameters (characteristic contours). By changing the basis of registration from external targets to intrinsic geometric features of the scanned objects, the system achieves both automatic operation and maintained precision.
Solution Approach 2:
Characteristic contours serve as intermediary elements that bridge different laser scans for automatic registration. These geometric features act as mediators that enable the evaluation unit to establish accurate transformations between scans without requiring manual targets, maintaining precision while simplifying operation.
4Reliability
If multiple targets are placed in the environment for registration, then the transformation calculation can be performed, but the device complexity and setup time increase
Solution Approach 1:
The patent extracts registration capability directly from the laser scanning process itself by identifying characteristic contours within the scanned data. This eliminates the separate target placement and measurement step, removing the complexity of managing physical targets while maintaining reliable transformation calculation through automated contour-based matching.
Data Source
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AI summary
The method involves creating two scans to be measured and an object from different scan positions (2, 4) using a three-dimensional (3D) laser scanner. Laser scans are stored in a project file, and the scan positions and an associated contour of the object are graphically represented on a display. The scan positions and the contours in the coverage are relatively positioned. An obtained overview is stored as a digital field book. The laser scans are linkable with one another, where a linkage displays a common overlapping area of the 3D to laser data of the linked scans. An independent claim is also included for a device for evaluating laser scans.