TheRacingSDC

Big Thanks to:

This is the project repo for the final project of the Udacity Self-Driving Car Nanodegree: Programming a Real Self-Driving Car. For more information about the project, see the project introduction here.

Please use one of the two installation options, either native or docker installation.

Native Installation

  • Be sure that your workstation is running Ubuntu 16.04 Xenial Xerus or Ubuntu 14.04 Trusty Tahir. Ubuntu downloads can be found here.

  • If using a Virtual Machine to install Ubuntu, use the following configuration as minimum:

    • 2 CPU
    • 2 GB system memory
    • 25 GB of free hard drive space

    The Udacity provided virtual machine has ROS and Dataspeed DBW already installed, so you can skip the next two steps if you are using this.

  • Follow these instructions to install ROS

  • Dataspeed DBW

  • Download the Udacity Simulator.

Docker Installation

Install Docker

Build the docker container

docker build . -t capstone

Run the docker file

docker run -p 4567:4567 -v $PWD:/capstone -v /tmp/log:/root/.ros/ --rm -it capstone

Port Forwarding

To set up port forwarding, please refer to the instructions from term 2

Prerequisite for Udacity VM with ROS pre-installed

Apply the following commands (one at a time)

echo "source /opt/ros/kinetic/setup.bash" >> ~/.bashrc
mkdir -p ~/catkin_ws/src
cd ~/catkin_ws/src
catkin_init_workspace
cd ~/catkin_ws
catkin_make

Prerequisite for Udacity Workspace

Apply the following commands (one at a time)

apt update
apt install ros-kinetic-dbw-mkz-msgs

ROS Architecture

ROS node architecture with the publish and subscribe topics.

alt text

Usage

  1. Clone the project repository
git clone https://github.com/hc167/Udacity-SDC-Term-Three-Capstone.git Capstone0
  1. Install python dependencies
cd Capstone0
pip install -r requirements.txt
  1. Make and run styx
cd ros
catkin_make -DCMAKE_BUILD_TYPE=Release
source devel/setup.sh
roslaunch launch/styx.launch
  1. Run the simulator

Real world testing

  1. Download training bag that was recorded on the Udacity self-driving car.
  2. Unzip the file
unzip traffic_light_bag_file.zip
  1. Play the bag file
rosbag play -l traffic_light_bag_file/traffic_light_training.bag
  1. Launch your project in site mode
cd CarND-Capstone/ros
roslaunch launch/site.launch
  1. Confirm that traffic light detection works on real life images