Lidar Signal Compression via Floating-Point to Integer Conversion
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Solution Overview
Problem
Current systems for storing and transmitting vehicle sensor data, such as LIDAR data, are inefficient due to the large bandwidth requirements of floating-point numbers, leading to ineffective memory storage and data transmission.
Innovation Solution
A system and method that converts floating-point sensor data to integer numbers based on a parameter set, including determining the bit length parameter, applying compression, and transmitting the compressed data, with the ability to decompress and reconstruct the original floating-point numbers for vehicle operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If floating-point numbers are used to represent sensor data, then measurement precision is improved, but bandwidth requirements increase and storage efficiency deteriorates
Solution Approach 1:
The patent changes the data representation parameter from floating-point format to a custom integer-based format. The system determines a bit length parameter based on the maximum and minimum values in the sensor data, then converts floating-point numbers to integers using this parameter. This parameter change reduces the storage requirements and bandwidth needs while maintaining sufficient precision for sensor data representation.
Solution Approach 2:
The patent extracts only the essential information needed for sensor data representation by determining the actual bit length required based on the data range (max and min values). Instead of using fixed floating-point representation, the system extracts the minimum necessary bits to represent the data, removing redundant information and reducing overall data volume for storage and transmission.
2Productivity
If data compression is applied to reduce bandwidth requirements, then transmission efficiency is improved, but information loss increases
Solution Approach 1:
The patent implements feedback by transmitting the parameter set (including bit length, maximum value, and minimum value) along with the compressed integer data. The receiving system uses this feedback information to accurately reconstruct the original floating-point values from the compressed integers, ensuring no information loss occurs during compression and transmission.
Solution Approach 2:
The patent performs preliminary analysis of the sensor data to determine the bit length parameter, maximum value, and minimum value before compression. This preliminary action allows the system to optimize the compression parameters specifically for the given data set, ensuring that the compression process preserves all necessary information while maximizing compression efficiency.
Data Source
AI summary
A system includes a processor and a memory. The memory stores instructions executable by the processor to receive sensor data including floating-point numbers. The memory stores instructions to convert the floating-point numbers to integer numbers based on a parameter set. The memory stores instructions to actuate a vehicle component based on the integer numbers.