Research on Autonomous Driving Perception based on Deep Learning Algorithm

被引：0

作者：

Zhou, Bolin ^{[1
]}

Zheng, Jihu ^{[1
]}

Chen, Chen ^{[1
]}

Yin, Pei ^{[2
]}

Zhai, Yang ^{[1
]}

机构：

[1] China Automot Technol & Res Ctr Co Ltd, Automot Data Ctr, Tianjin 300393, Peoples R China

[2] Changan Univ, Sch Automobile, Xian 710000, Shanxi, Peoples R China

来源：

2019 INTERNATIONAL CONFERENCE ON IMAGE AND VIDEO PROCESSING, AND ARTIFICIAL INTELLIGENCE | 2019年 / 11321卷

关键词：

Perception Technology; Deep Learning; Image Recognition; Point Cloud Recognition; Fusion Filtering;

D O I：

10.1117/12.2539133

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Multiple source sensor fusion is the foundation of motion planning for autonomous driving system, which is the crucial part in improving the performances for unmanned operational system. In this article, based on the deep learning platform CATARC constructed, applied with Udacity's Lincoln MKZ multiple sensor data, implemented with Robotic Operation System, Computer Vision, PointCloud Library, Deep Neural Networks and Extended Kalman Filter, constructed a low-cost object pose estimation data fusion solution, aiming at technic support for the industrialization of autonomous driving technologies.

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