Skip to content

Homeworks for the Autonomous Driving course by pony.ai in the spring term 2019.

Notifications You must be signed in to change notification settings

xumingkuan/Autonomous-Driving-2019

 
 

Repository files navigation

Public course from pony.ai

In this course you'll learn basic knowledge about autonomous car and complete essential algorithms in autonomous car simulation system. In next weeks, you'll get some real data recorded during our road test. Your task is writing code to recognise around obstacles, plan a best path to avoid them and make autonomous car run along the road for its destination.

You can access the code and document for homework here.

Let's begin now!!!

System setup

A shared display library with some utility classes has been introduced into the codebase. We will provide several visualization tools based on this tool. To use this tool, you need to run following commands to install several system dependencies.

sudo apt install qtdeclarative5-dev clang-3.8 nasm

QT is a cross-platform application framework. Our visualization tools will be developed based on it.

Clang is the compiler we use to build the libraries. We require you to install clang-3.8 to avoid any potential issues caused by compiler version.

nasm is a required library for an introduced third-party library.

Visualization Issue Troubleshooting

Our visualization tool is based on OpenGL 3D rendering. We recommend using Ubuntu16.04 native system to get the best visualization effect, since 3D acceleration inside virtual machines is just experimental features. If you must use virtual machine for some reasons, we recommend VirtualBox, which is free and cross-platform.

If you are using VMWare and 3D rendering is not correct, please try command export SVGA_VGPU10=0 to set an environment variable, and re-run the binary again to check if it solves your issue.

About

Homeworks for the Autonomous Driving course by pony.ai in the spring term 2019.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • C++ 85.7%
  • Python 8.7%
  • Mathematica 5.5%
  • Other 0.1%