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.

引用

页数：5

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