Mapping Data Suitability Assessment via Ground Control Points
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Solution Overview
Problem
Map content providers face challenges in achieving high accuracy and reliability in digital mapping due to errors in sensor data, particularly in complex urban environments, where GPS signals can be distorted, leading to localization errors and insufficient data for accurate path planning and collision avoidance in autonomous vehicles.
Innovation Solution
A method and system for identifying suitable data for mapping by receiving images, selecting ground control points, determining their perceived locations, computing pairwise distances, and comparing these distances to assess the suitability of the images for mapping, enabling real-time data correction and improvement of mapping accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If GPS signals are used for localization in complex urban environments, then mapping coverage is expanded, but localization accuracy deteriorates due to signal distortion
Solution Approach 1:
The patent introduces image data as an intermediary medium to bridge the gap between GPS coverage and localization accuracy. Images serve as a mediator that can be processed to extract visual features and compute positions independently of GPS signals, thereby maintaining both broad coverage and high accuracy in GPS-denied urban environments.
Solution Approach 2:
The patent replaces the mechanical/electromagnetic GPS positioning system with a computational vision-based system. By using image processing algorithms to detect features and calculate positions, the system substitutes the traditional GPS mechanism with a software-based solution that achieves comparable or superior accuracy in challenging environments.
2Measurement precision
If multiple sensors are used to improve localization accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent extracts the localization function from the complex multi-sensor system and implements it solely through image processing. By taking out the computational vision component and making it the primary localization mechanism, the system achieves high accuracy while reducing overall device complexity compared to integrating multiple sensors.
Solution Approach 2:
The patent makes image data serve multiple functions: it provides both the mapping information and the localization data simultaneously. This multi-functionality eliminates the need for separate sensors dedicated to each function, thereby reducing device complexity while maintaining or improving measurement precision.
3Measurement precision
If sensor data is processed to achieve high accuracy, then measurement precision is improved, but processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary actions by pre-processing image data to extract and store visual features and their positions before actual localization is needed. This pre-computation allows for faster localization processing during execution, as the system only needs to match pre-extracted features rather than processing raw images in real-time, thereby reducing processing time while maintaining high accuracy.
Data Source
AI summary
Systems and methods for identifying data suitable for mapping are provided. In some aspects, the method includes receiving one or more images acquired in an area of interest, and selecting at least two ground control points within a field of view of the one or more images. The method also includes determining perceived locations for the at least two ground control points using the one or more images, and computing pairwise distances between the perceived locations and predetermined locations of the at least two ground control points. The method further includes comparing corresponding pairwise distances to identify differences therebetween, and determining a suitability of the one or more images for mapping based on the comparison.