LiDAR Calibration via High-Resolution Data Conversion
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current calibration methods between cameras and LiDAR sensors face errors due to mismatched feature points and are challenging with low-cost, low-resolution LiDAR sensors, which lack accurate 3D information for precise calibration.
Innovation Solution
A system and method for high-resolution conversion of LiDAR data to accurately derive feature points, involving a data reception unit, feature point extraction unit, conversion information derivation unit, and data fusion unit to fuse image and LiDAR data, enhancing the recognition rate of feature points and improving calibration accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If low-cost low-resolution LiDAR sensor is used, then cost and power consumption are reduced, but measurement precision of feature points deteriorates
Solution Approach 1:
The patent introduces an intermediary process of high-resolution conversion that transforms low-resolution LiDAR data into high-resolution data before feature point extraction. This intermediary step allows the system to use low-cost sensors while achieving high measurement precision through data transformation rather than hardware upgrade
Solution Approach 2:
The patent changes the resolution parameter of LiDAR data through high-resolution conversion. By transforming the data from low-resolution to high-resolution state, the system improves feature point detection accuracy without changing the physical sensor hardware, thus maintaining low cost and power consumption
2Device complexity
If traditional calibration method mapping 3D LiDAR points to 2D camera image is used, then calibration process is simplified, but calibration accuracy deteriorates due to feature point mismatch
Solution Approach 1:
The patent transforms the calibration approach by converting 3D LiDAR data into 2D high-resolution data that matches the camera image dimensionality. This dimensional transformation enables direct feature point comparison between LiDAR and camera without the traditional 3D-to-2D projection mapping, improving calibration accuracy while maintaining process simplicity
Solution Approach 2:
The patent creates a high-resolution copy of the LiDAR point cloud data that corresponds to the camera image resolution. This copying approach allows direct feature point extraction and matching without complex 3D projection calculations, improving both calibration accuracy and computational efficiency
Data Source
AI summary
A system and method of calibrating a camera and a LiDAR sensor through high-resolution conversion of LiDAR data is proposed. The system is included a data reception unit for receiving at least one image data and LiDAR data, which are obtained by photographing a target object, from the respective camera and LiDAR sensor, a feature point extraction unit for extracting feature points of each of the received image data and LiDAR data, a conversion information derivation unit for deriving image conversion information for fusing the feature points of each image data, and deriving LiDAR conversion information for fusing the feature points of each LiDAR data, and a data fusing unit for fusing at least two feature points of the image data, and fusing at least two feature points of the LiDAR data, thereby fusing the fused feature points of the image data and LiDAR data.