LiDAR Surface Feature Data Generation via Triangulation and Gap Filling
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Solution Overview
Problem
Generating accurate surface feature data for roadways from LiDAR scans is challenging due to varying widths and heights of roadways, missing data, and the difficulty in assigning heights to vertices of planar surfaces.
Innovation Solution
A method and system that involve receiving LiDAR data, extracting input layers, dilating and unionizing them, eroding and triangulating to generate planar surfaces, assigning heights to vertices, detecting incomplete features, and filling them to create accurate surface feature data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If LiDAR data is used to generate surface feature data, then three-dimensional mapping capability is improved, but data completeness and accuracy deteriorate due to missing or incomplete roadway features
Solution Approach 1:
The patent applies preliminary action by performing dilation and unionization operations on input layers before generating the final surface feature data. This preprocessing step fills in gaps and incomplete features in advance, ensuring that missing roadway data is recovered before the main triangulation and height assignment processes occur.
Solution Approach 2:
The patent uses an intermediary approach by introducing a filling operation that acts as a mediator between the incomplete LiDAR data and the final surface feature model. This filling step interpolates missing features using surrounding data points, effectively bridging gaps in the roadway representation.
2Shape
If roadway features are represented by polygons with vertices, then geometric representation is improved, but difficulty in assigning heights and handling varying widths increases processing complexity
Solution Approach 1:
The patent applies segmentation by dividing the roadway surface into multiple triangular planar surfaces through triangulation. This breaks down the complex problem of height assignment for varying width roadways into smaller, manageable triangular elements, where height can be assigned to vertices more systematically.
Solution Approach 2:
The patent transitions from two-dimensional polygon representation to three-dimensional triangular planar surfaces by assigning height values to vertices. This dimensionality change allows the system to represent varying roadway widths and heights more accurately while providing a structured approach to height assignment through the triangulation framework.
3Manufacturing precision
If accurate surface feature data is generated, then modeling accuracy is improved, but processing time and computational effort increase
Solution Approach 1:
The patent uses segmentation through triangulation to divide the roadway surface into smaller triangular elements. This allows parallel processing of individual triangles and vertices, improving computational efficiency while maintaining high modeling accuracy for the complete surface.
Solution Approach 2:
The patent performs preliminary dilation and unionization operations to complete incomplete features before the main processing stages. By filling gaps early in the process, the system reduces the need for iterative corrections later, thereby improving overall processing efficiency while ensuring accurate surface representation.
Data Source
AI summary
Methods and systems for generating surface feature data may include receiving a data set, extracting input layers from the data set, dilating and unionizing the input layers, and eroding and triangulating the input layers to generate a plurality of planar surfaces. The methods and systems may further include assigning heights to each vertex of the plurality of planar surfaces, detecting incomplete features in the plurality of planar surfaces, and filling the incomplete features in the plurality of planar surfaces.