Multi-LiDAR Ranging Calibration for Autonomous Driving
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Solution Overview
Problem
The measurement range of existing laser radar ranging devices is smaller than the distance range measured by visual image algorithms, leading to inadequate calibration efficiency and accuracy for autonomous driving systems.
Innovation Solution
A ranging method using a laser radar system that receives data from multiple laser radars to establish a three-dimensional coordinate model, determining distances between a target unmanned device and obstacles, and sending this information for visual image algorithm calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single laser radar is used for ranging calibration, then the device complexity is low, but the measurement range is limited and calibration efficiency is low
Solution Approach 1:
The patent combines multiple laser radars into a unified calibration system. Each laser radar measures distances to the same obstacle from different positions, and their data are integrated through coordinate transformation to achieve a comprehensive measurement range that exceeds any single laser radar's capability.
Solution Approach 2:
The calibration process is segmented into multiple independent laser radar measurements that can be performed simultaneously or sequentially. Each laser radar independently measures distances to obstacles, and the results are combined through coordinate system transformations to form a complete calibration dataset.
2Productivity
If multiple laser radars are used to expand measurement range, then the measurement range increases, but the device complexity increases
Solution Approach 1:
The system establishes a universal coordinate transformation framework that can handle data from any number of laser radars positioned at different locations. This multi-functional approach allows the same processing methodology to be applied regardless of the number of sensors, improving calibration efficiency without proportionally increasing complexity.
Solution Approach 2:
The patent uses coordinate copying and transformation to virtualize the measurement positions. Instead of physically moving a single laser radar to multiple positions, the system copies measurement data from multiple fixed laser radars and transforms them into a unified coordinate system, achieving the effect of multiple positions with standardized processing.
3Measurement precision
If visual image algorithm is used for distance calculation, then the measurement range is large, but the accuracy cannot be guaranteed
Solution Approach 1:
The patent introduces multiple laser radars as intermediary measurement devices between the visual image algorithm and the ground truth. The laser radars provide accurate intermediate measurements that bridge the gap between the empirical visual algorithm and actual distances, enabling calibration across the full measurement range without sacrificing accuracy.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method enhances calibration efficiency and accuracy by enabling ranging calibration over a larger distance range compared to single laser radar systems.
Implementation Method 1
receiving ranging data obtained by measuring via a plurality of laser radars of the laser radar system
Data Source
AI summary
A ranging method based on a laser radar system, a device and a readable storage medium are provided. The ranging method includes receiving ranging data obtained by measuring via a plurality of laser radars of a laser radar system, where the ranging data includes distances between the laser radars and obstacles in measurement ranges of the laser radars; establishing a three-dimensional coordinate model according to the ranging data; and determining a distance between a target unmanned device and each obstacle according to the three-dimensional coordinate model. The ranging method can realize a ranging calibration task for a larger distance range, thereby effectively improving a calibration efficiency and accuracy of the visual image algorithm, compared with the existing method of ranging calibration of the visual image algorithm by a single laser radar.