Laser Radar Internal Parameter Precision Detection via Road Thickness
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Solution Overview
Problem
The internal parameters of laser radars, such as pose and emission angle, set by factory calibration may not meet accuracy requirements due to manufacturing errors, leading to imprecise performance in high-precision map drawing and automatic driving, resulting in poor user experience.
Innovation Solution
A method and device that utilize point cloud data from an autonomous mobile carrier to reconstruct a three-dimensional scene, divide the scene to isolate road data, and determine road thickness to assess the precision of the laser radar's internal parameters, providing an automated way to detect parameter accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If factory calibration is used to set internal parameters, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The system performs self-diagnosis by automatically detecting internal parameter precision through point cloud data analysis. The laser radar system calibrates itself by comparing measured road thickness against expected values, eliminating the need for complex external calibration procedures while maintaining high measurement precision.
Solution Approach 2:
The system implements a feedback mechanism where point cloud data is continuously analyzed to detect deviations in internal parameters. The detected precision information feeds back to indicate whether calibration is needed, creating a closed-loop system that maintains accuracy without complex manual intervention.
2Productivity
If automated detection method is implemented, then productivity is improved, but device complexity increases
Solution Approach 1:
The point cloud processing system serves multiple functions: it captures environmental data for navigation, analyzes road thickness for precision detection, and provides calibration feedback. This multi-functionality enables automated precision detection without requiring separate dedicated hardware, thus improving productivity while limiting complexity increase.
3Measurement precision
If point cloud data processing is used for precision detection, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system extracts only the essential information needed for precision detection from the point cloud data - specifically focusing on road surface points and thickness measurements. By extracting only relevant data rather than processing the entire point cloud, the system achieves high measurement precision while minimizing processing time.
Data Source
AI summary
Embodiments of the present disclosure provide a method and a device for detecting a precision of an internal parameter of a laser radar, a related apparatus and a medium. The method may include the following steps. Point cloud data collected by the laser radar arranged on an autonomous mobile carrier travelling on a flat road is obtained. A three-dimensional scene reconstruction is performed based on the point cloud data collected to obtain a point cloud model of a three-dimensional scene. The point cloud model of the three-dimensional scene is divided to obtain the road. A thickness of the road is determined based on the point cloud data of the road. It is determined whether the internal parameter of the laser radar is precise based on the thickness of the road.