Traffic Light Positioning via Multi-Scanner Point Cloud Fusion
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Solution Overview
Problem
Unmanned vehicles face challenges in accurately identifying traffic lights due to external factors like light and rain, necessitating improved methods for generating precise position information of traffic signals.
Innovation Solution
A method and device that utilize target and reference scanners to obtain point cloud data, calculate Euler angles, and generate position information of traffic lights by partitioning point clouds into cubes, fitting planes, and determining optimal Euler angle differences between scanners, ultimately converting data into accurate position information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional sensor-based identification methods are used for traffic lights, then the system structure is simple, but the identification accuracy deteriorates under external factors like light and rain
Solution Approach 1:
The patent segments the traffic light identification process into multiple stages: data collection from multiple scanners, coordinate system transformation, Euler angle calculation, and position determination. This segmentation allows each stage to be optimized independently, improving overall accuracy while managing system complexity through modular processing
Solution Approach 2:
The patent introduces intermediate coordinate systems and Euler angles as mediators between the raw scanner data and the final traffic light position. These intermediaries enable precise mathematical transformation and calculation, bridging the gap between sensor measurements and accurate position identification under adverse conditions
2Measurement precision
If multiple scanners are deployed to improve position information accuracy, then measurement precision improves, but device complexity and data processing complexity increase
Solution Approach 1:
The patent establishes a universal coordinate transformation framework that can process data from multiple scanners (target scanner, reference scanner, mobile scanner) using the same mathematical models. This multi-functional approach allows the system to handle various scanner configurations and positions through a single unified method, improving position accuracy without proportionally increasing processing complexity
Solution Approach 2:
The patent transforms the complex multi-scanner data into standardized parameters (Euler angles, coordinate transformations) that simplify the integration process. By changing the representation parameters from raw scanner coordinates to transformed coordinate systems with defined Euler angles, the system manages complexity while maintaining high measurement precision
Data Source
AI summary
Disclosed embodiments include a method and a device for generating position information of a target object. In some embodiments, the method comprises: obtaining target point cloud data of the target object, acquired by a target scanner at a target position, and position information of the target scanner, and obtaining reference point cloud data of the target object, acquired by a reference scanner at a reference position, and position information and an Euler angle of the reference scanner; obtaining an Euler angle of the target scanner based on the target point cloud data, the reference point cloud data, and the Euler angle of the reference scanner; and generating the position information of the target object based on the target point cloud data, the position information and the Euler angle of the target scanner, the reference point cloud data, and the position information and the Euler angle of the reference scanner.