Point Cloud Target Removal After LiDAR Scan Matching
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Solution Overview
Problem
Existing techniques struggle to efficiently eliminate point cloud data related to matching targets after the completion of the matching process between sets of point cloud data obtained from different viewpoints, especially when the target object has a complicated shape or exceeds the measurement range of the device.
Innovation Solution
A surveying data processing device and method that detects and integrates point cloud data using matching targets, sets a tubular space to contain the targets, and eliminates point cloud data within this space, utilizing a processor to determine correspondence relationships and set dimensions for the tubular space.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If point cloud data of matching target is retained for matching process, then matching accuracy is improved, but data processing efficiency deteriorates due to unnecessary data retention
Solution Approach 1:
The patent applies preliminary action by detecting and identifying matching targets in point cloud data before the matching process is completed. The system detects points with high reflection intensity that match the predetermined reflection characteristic, identifies them as matching targets, and eliminates their point cloud data before final integration. This preliminary elimination of unnecessary data improves processing efficiency while maintaining matching accuracy during the matching process.
2Productivity
If point cloud data of matching target is eliminated early, then data processing efficiency is improved, but matching accuracy deteriorates due to insufficient matching reference
Solution Approach 1:
The system performs preliminary detection and identification of matching targets using their unique reflection characteristics before elimination. By detecting points with reflection intensity meeting the predetermined threshold and identifying them as matching targets, the system ensures that matching can be performed accurately using these identified targets, and only after matching is complete are the target points eliminated from the integrated data.
3Quantity of substance
If all point cloud data is retained after integration, then data completeness is improved, but storage requirements and processing load increase
Solution Approach 1:
The patent applies the extraction principle by removing the matching target points from the integrated point cloud data after the matching process is completed. The system extracts and eliminates points that correspond to matching targets based on their identified locations, retaining only the necessary measurement object data. This reduces storage requirements and processing load while maintaining the completeness of the actual measurement data.
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
Efficiently removes point cloud data related to matching targets, ensuring accurate integration and elimination of unnecessary data, thereby enhancing the precision and completeness of the integrated point cloud data.
Implementation Method 1
laser light is emitted on an object, and the laser light that is reflected back from the object is measured
Implementation Method 2
These techniques are called 'LiDAR (Light Detection and Ranging, Laser Imaging Detection and Ranging)'
Implementation Method 3
detect, among the first point cloud data and second point cloud data, light in which an intensity of light is a predetermined value or greater, as reflection light that is reflected back from the matching target
Data Source
Figure 1~2
Figure 3
AI summary
Point cloud data relating to a matching target is efficiently eliminated after completion of a process of matching between sets of point cloud data obtained at different viewpoints. The surveying data processing device includes a target detecting unit, a location acquiring unit, a point cloud data eliminating region setting unit, and a point cloud data eliminating unit. The target detecting unit detects a target in point cloud data. The point cloud data is obtained by emitting laser light on an object having the target and by detecting the light reflected back from the object. The target location acquiring unit acquires a location of the detected target. The point cloud data eliminating region setting unit sets a point cloud data eliminating region containing the target, based on the location of the target. The point cloud data eliminating unit eliminates point cloud data contained in the point cloud data eliminating region.