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http://dx.doi.org/10.6109/jkiice.2021.25.12.1859

Semantic Depth Data Transmission Reduction Techniques using Frame-to-Frame Masking Method for Light-weighted LiDAR Signal Processing Platform  

Chong, Taewon (CARNAVICOM. Co., Ltd.)
Park, Daejin (School of Electronic Engineering, Kyungpook National University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.25, no.12, 2021 , pp. 1859-1867 More about this Journal
Abstract
Multi LiDAR sensors are being mounted on autonomous vehicles, and a system to multi LiDAR sensors data is required. When sensors data is transmitted or processed to the main processor, a huge amount of data causes a load on the transport network or data processing. In order to minimize the number of load overhead into LiDAR sensor processors, only semantic data is transmitted through data comparison between frames in LiDAR data. When data from 4 LiDAR sensors are processed in a static environment without moving objects and a dynamic environment in which a person moves within sensor's field of view, in a static experiment environment, the transmitted data reduced by 89.5% from 232,104 to 26,110 bytes. In dynamic environment, it was possible to reduce the transmitted data by 88.1% to 29,179 bytes.
Keywords
LiDAR sensor; Embedded system; Parallel processing; Low-power signal processing;
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