Variable Range Interval LIDAR Compression
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Solution Overview
Problem
Conventional LIDAR systems face inefficiencies in data compression due to constant range interval sizes, which lead to unnecessary precision and storage inefficiencies, especially when dealing with non-constant uncertainty models.
Innovation Solution
Implementing a compression module that uses range equivalence intervals with sizes dependent on the associated range values, allowing for more efficient mapping of range data to integers without loss of accuracy, thereby reducing storage requirements and improving data transfer efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If constant range interval sizes are used for compression, then measurement precision is maintained, but storage efficiency deteriorates
Solution Approach 1:
The patent applies local quality by using variable range interval sizes that adapt to local uncertainty characteristics. Different range values are mapped to different interval sizes based on their associated uncertainty models, allowing finer precision where needed and coarser intervals where uncertainty is higher, thus optimizing the balance between measurement precision and storage efficiency
Solution Approach 2:
The patent changes the parameter of range interval size from constant to variable based on uncertainty models. By mapping range values to integers using non-uniform interval sizes that reflect uncertainty characteristics, the system achieves better compression ratios while maintaining accuracy where it matters most
2Device complexity
If constant range interval sizes are used for compression, then device complexity is reduced, but productivity deteriorates
Solution Approach 1:
The patent implements local quality by applying different interval size strategies to different range regions. The compression algorithm uses uncertainty models to determine appropriate interval sizes locally, improving data transfer efficiency without requiring overly complex global optimization mechanisms
Solution Approach 2:
The patent introduces dynamics by making the range interval size adaptive rather than static. The compression algorithm dynamically selects interval sizes based on uncertainty characteristics of different range values, enabling better productivity while keeping the mechanism relatively simple through rule-based adaptation
Data Source
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AI summary
A laser imaging, detection, and ranging (LIDAR) system may include a scanner and a compression module. The scanner may be configured to generate a scan including multiple range values associated with multiple scan points of the scan. The compression module may be configured to map multiple range values to multiple integers. The multiple integers may represent multiple range intervals. The multiple range intervals may include multiple differently sized range intervals. The size of the range intervals may be a function of range according to an interval size function.