LiDAR Receiving Array Grouping for Range-Based Storage Reduction
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Solution Overview
Problem
The increasing precision of LiDAR systems in autonomous driving results in a significant increase in detection data volume, leading to a storage space challenge.
Innovation Solution
The receiving units in a LiDAR array are grouped according to a preset rule, with customized measurement ranges and storage spaces set for each group based on detection requirements, reducing unnecessary data acquisition and optimizing storage usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the measurement range is increased to meet detection requirements, then the detection capability is improved, but the storage space required increases significantly
Solution Approach 1:
The receiving units are divided into multiple groups, with each group assigned a different measurement range according to specific detection requirements. This segmentation allows the system to optimize storage space by only collecting data within necessary ranges for each group, rather than uniformly collecting data across the entire measurement range for all receiving units.
Solution Approach 2:
Different measurement ranges and sampling rates are assigned to different groups of receiving units based on their specific detection needs. This local quality approach ensures that each group operates with optimal parameters for its function, improving overall system efficiency while reducing total data volume and storage requirements.
2Measurement precision
If the sampling rate is increased to improve measurement precision, then the detection accuracy is improved, but the data volume and storage requirements increase
Solution Approach 1:
The sampling rate is set dynamically and differently for each group of receiving units based on their specific detection requirements. This dynamic parameter configuration allows the system to achieve necessary detection accuracy for each group without uniformly applying high sampling rates across all receiving units, thereby reducing overall data volume while maintaining required precision.
3Device complexity
If the measurement range is set uniformly for all receiving units, then the system simplicity is maintained, but the storage space is wasted on unnecessary data
Solution Approach 1:
The receiving units are segmented into multiple groups with different measurement ranges configured for each group. This segmentation strategy balances system complexity and storage efficiency by implementing a structured, modular configuration approach that is manageable while significantly reducing wasted storage space compared to uniform configuration.
Data Source
AI summary
This application provides a parameter configuration method, device, and non-transitory computer-readable storage medium. In this method, the receiving units in the LiDAR receiving array are grouped according to a preset rule. Then, based on the detection requirements, the measurement range corresponding to each group of receiving units is set. Based on the measurement range of each group of receiving units, the storage space for each group of receiving units is set. The storage space is used to store the measurement data of each group of receiving units. Thus, the method reduces the acquisition of measurement data by some receiving units in unnecessary measurement ranges, decreases the volume of measurement data, and saves storage space.