Multi-LiDAR Point Cloud Alignment Using Common-Region Detection
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Solution Overview
Problem
Existing LiDAR systems face challenges in accurately integrating three-dimensional data from multiple points due to blind spots caused by obstructions, leading to incorrect representation of the monitored object when aligning point cloud data.
Innovation Solution
A measurement apparatus and method that utilize a position specifying unit to align data using an apparatus reference coordinate system, a candidate specifying unit to identify common regions, and a common region determining unit to determine regions for accurate integration of point cloud data across multiple LiDAR devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If point cloud data from multiple measurement points are integrated by projecting on the ground and performing correction to align orientation of characteristic structures, then blind spot regions can be supplemented and data coverage is improved, but objects with similar structures may be incorrectly aligned and data accuracy deteriorates
Solution Approach 1:
The patent introduces a ground plane as an intermediary reference surface. By projecting measurement apparatus positions and candidate regions onto the ground plane, the system creates a stable intermediate representation that facilitates accurate spatial relationship determination without directly aligning similar structures, thus avoiding incorrect alignment while maintaining data coverage.
Solution Approach 2:
The patent transforms the three-dimensional point cloud alignment problem into a two-dimensional ground plane projection problem. By working in the ground plane dimension rather than directly in 3D space, the system determines candidate regions and performs alignment in a simplified dimension, then applies results back to the original 3D data, improving both coverage and accuracy.
2Productivity
If correction is performed to align orientation of objects with similar rectilinear features, then data from multiple measurement points can be integrated, but the objects may be incorrectly aligned and do not correctly represent the monitored target
Solution Approach 1:
The patent applies different processing qualities to different spatial regions. Candidate regions are identified with specific spatial characteristics and processed differently from other regions. By determining candidate regions based on ground plane projections and spatial relationships rather than uniform structure alignment, the system ensures high reliability in critical regions while maintaining overall data integration productivity.
3Measurement precision
If LiDAR is used to measure distance to objects, then three-dimensional data can be acquired, but blind spots are created behind buildings where light is blocked and data is missing
Solution Approach 1:
The patent performs preliminary positioning of measurement apparatus on the ground plane and preliminary identification of candidate regions before actual point cloud integration. By pre-establishing the spatial framework and candidate regions in the ground plane, the system prepares the infrastructure needed to effectively integrate data from multiple points and supplement blind spot regions, reducing information loss while maintaining measurement precision.
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
Enables precise alignment and integration of three-dimensional data from multiple LiDAR devices, correcting for blind spots and ensuring accurate representation of the monitored object.
Implementation Method 1
The LiDAR-equipped monitoring apparatus measures the distance to the object to be monitored based on the time it has taken from emission of light to reception of the reflected light and the speed of the light.
Data Source
AI summary
A measurement apparatus according to the present disclosure includes a position specifying unit configured to specify, using an apparatus reference coordinate system having a position of the measurement apparatus set as a reference, a position of each of a plurality of other measurement apparatuses; a candidate specifying unit configured to extract at least three measurement apparatuses out of the measurement apparatus and the plurality of the other measurement apparatuses and to specify, based on the positions of the extracted measurement apparatuses, a candidate region that serves as a candidate of a common region referred to in performing alignment of data captured by the measurement apparatus and the plurality of the other measurement apparatuses; and a common region determining unit configured to determine the common region based on the distribution of the plurality of the candidate regions obtained by changing combinations of the measurement apparatuses to be extracted.