PyRoboCar: A Low-cost Deep Neural Network-based Autonomous Car

被引：0
|
作者：
Hendry, Gordon [1 ]
Harris, Seth [1 ]
Goodwin, Ryan [1 ]
Neverov, Leonid [1 ]
Xiao, Yunkai [2 ]
Tian, David [3 ]
Song, Yang [1 ]
机构：
[1] Univ North Carolina Wilmington, Wilmington, NC 28407 USA
[2] North Carolina State Univ, Raleigh, NC 27695 USA
[3] Google LLC, Mountain View, CA 94043 USA
来源：
2021 IEEE FRONTIERS IN EDUCATION CONFERENCE (FIE 2021) | 2021年
关键词：
Autonomous car; educational robotics; deep learning;
D O I：
10.1109/FIE49875.2021.9637429
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this innovative practice WIP paper, we present PyRoboCar, a low-cost deep neural network- based autonomous car project. PyRoboCar is a small-scale replication of a real self-driving car using a deep convolutional neural network (CNN), which takes images from a front fisheye camera as input and produces car steering angles as output. PyRoboCar uses a similar network architecture as industry-level autonomous cars and can drive itself in real-time using a camera, an additional Tensor Processing Unit, and a Raspberry Pi 4 platform. We have also made this project open online, including the code and instructions.
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页数：5
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