Map Error Quantification via Point Cloud Registration
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Solution Overview
Problem
Current navigation systems face challenges in accurately quantifying map errors, which can lead to navigation inaccuracies and safety issues.
Innovation Solution
The method involves receiving two different map datasets of the same geographic location, dividing roads into segments, creating bounding boxes around these segments, and executing point cloud registration to align data points from both maps, thereby determining relative map errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If map data from multiple sources is used for navigation, then navigation coverage and data availability are improved, but map accuracy and reliability deteriorate due to unquantified errors between different map sources
Solution Approach 1:
The patent replaces subjective map quality assessment with objective mathematical computation. Point cloud registration algorithms and error quantification metrics transform qualitative map differences into quantitative measurements, enabling automated comparison and selection of optimal map sources without human intervention.
Solution Approach 2:
The system introduces map error quantification metrics as an intermediary between multiple map sources and the navigation system. These metrics serve as a bridge that translates raw map data from different sources into comparable error values, allowing the navigation system to select or fuse maps based on quantified reliability rather than raw data alone.
2Measurement precision
If detailed map error analysis is performed across entire geographic areas, then map accuracy is improved, but computational complexity and processing time increase significantly
Solution Approach 1:
The patent divides the geographic area into multiple tiles or segments, allowing error quantification to be performed independently on smaller subsets of map data. This segmentation reduces the computational burden of processing entire geographic areas while maintaining overall accuracy through systematic aggregation of segment-level results.
Solution Approach 2:
The system performs error quantification selectively on specific map features or regions that are most critical for navigation, rather than uniformly analyzing all map data. This partial action approach focuses computational resources on high-impact areas where map errors most affect navigation safety.
3Measurement precision
If extensive point cloud registration and alignment processes are executed to compare map data, then map error measurement precision is improved, but processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary alignment and rough registration of map tiles from different sources before conducting detailed error quantification. This preliminary action establishes a coarse coordinate framework that reduces the complexity of subsequent precise error measurements, avoiding the need for exhaustive alignment procedures.
Solution Approach 2:
The system dynamically adjusts registration parameters and error quantification thresholds based on the specific characteristics of map data being compared. By changing parameters such as tolerance levels, sampling densities, and transformation precision, the system optimizes the balance between measurement accuracy and processing efficiency for different geographic contexts.
Data Source
AI summary
A method for quantifying map errors includes receiving first map data and second map data. The method includes receiving a road topographic map. The method further includes dividing the road into road segments. The method further includes creating a plurality of bounding boxes for each of the plurality of road segments. The method includes creating a first map tile and a second map tile by filtering out the bounding boxes. The method includes executing point cloud registration to align the plurality of first data points in the first map tile with the plurality of second data points in the second map tile to determine a plurality of absolute offsets between the plurality of first data points and the plurality of second data points. The method includes determining a relative map error between the first map and the second map based on the absolute offsets.