RADAR Data Compression for High-Definition Map Creation
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Solution Overview
Problem
Current systems for generating map data and performing localization in autonomous vehicles and machines using sensor data, such as RADAR and LIDAR, face challenges in efficiently processing and communicating large data sets while maintaining accuracy and precision.
Innovation Solution
The system compresses RADAR data by aggregating and quantizing point clouds, determining tile deltas, and encoding these changes to reduce data transmission, while also using localization engines to determine pose parameters for accurate mapping and navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If sensor data is transmitted without compression, then data accuracy is maintained, but data transmission volume increases
Solution Approach 1:
The patent extracts and transmits only the essential features and changes in sensor data rather than the complete raw data. By identifying and removing redundant information while preserving critical data characteristics, the system reduces transmission volume without sacrificing accuracy in the transmitted information.
Solution Approach 2:
The patent transforms sensor data from raw format to a compressed representation by changing parameters such as data resolution, aggregation levels, and feature extraction methods. This parameter transformation enables reduced data volume while maintaining the essential information needed for map creation and localization.
2Quantity of substance
If compression operations are performed on sensor data, then data transmission volume is reduced, but processing complexity increases
Solution Approach 1:
The patent divides sensor data into discrete point clouds and processes them in segmented units. By breaking down the continuous sensor stream into manageable segments that can be independently compressed and transmitted, the system reduces overall processing complexity while achieving effective data compression.
Solution Approach 2:
The patent performs preliminary compression and feature extraction operations on sensor data before transmission. By pre-processing the data to remove redundancy and extract essential features in advance, the system reduces the complexity of subsequent processing at the receiving end while maintaining data quality.
Data Source
AI summary
One or more embodiments of the present disclosure may relate to communicating RADAR (RAdio Detection And Ranging) data to a distributed map system that is configured to generate map data based on the RADAR data. In these or other embodiments, certain compression operations may be performed on the RADAR data to reduce the amount of data that is communicated from the ego-machines to the map system.