Free-Space Estimation for Self-Driving System using Millimeter Wave Radar and Convolutional Neural Network

被引：0

作者：

Aihara, Ryota ^{[1
]}

Fujimoto, Yasutaka ^{[1
]}

机构：

[1] Yokohama Natl Univ, Dept Phys Elect & Comp Engn, Yokohama, Kanagawa, Japan

来源：

2019 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS (ICM) | 2019年

关键词：

self-driving; millimeter wave radar; LIDAR; free space; Convolutional Neural Network; VISION;

D O I：

10.1109/icmech.2019.8722937

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Recently, autonomous vehicles are gaining a lot of attention and their R&D are conducted in various institutions. A vehicle should be able to change lanes for achieving full autonomous status. Using millimeter wave radar is cost-effective however it detects only a few points. To solve this problem, we propose a method to approximate free space generated by millimeter wave radar data to the free space generated by LIDAR data using CNN. The result shows that CNN enables to close to the LIDAR by an average of 1.5 m.

引用

页码：467 / 470

页数：4

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