TheRacingSDC

• Hiu Chan - Team Lead (hiu_chan@hotmail.com)
• Yuda Wang (yuda@berkeley.edu)
• Ran Yan (896521722@qq.com)
• Zhening (Sirius) Zhang (zznzhang@ucdavis.edu)
• Praveen Kumar Marothu (praveen.marothu@gmail.com)

Youtube Video Demo: https://www.youtube.com/watch?v=h8KuF9HO1Jw

Big Thanks to:

• https://github.com/leggedrobotics/darknet_ros , darknet_ros, which is used in the project.
• And https://pjreddie.com/darknet/yolo/ , Joseph Redmon, the original author of darknet & YOLO.

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

  • ROS Kinetic if you have Ubuntu 16.04.
  • ROS Indigo if you have Ubuntu 14.04.

• Dataspeed DBW

  • Use this option to install the SDK on a workstation that already has ROS installed: One Line SDK Install (binary)

• 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.

Usage

1. Clone the project repository

git clone https://github.com/hc167/Udacity-SDC-Term-Three-Capstone.git Capstone0

2. Install python dependencies

cd Capstone0
pip install -r requirements.txt

3. Make and run styx

cd ros
catkin_make -DCMAKE_BUILD_TYPE=Release
source devel/setup.sh
roslaunch launch/styx.launch

4. 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

3. Play the bag file

rosbag play -l traffic_light_bag_file/traffic_light_training.bag

4. Launch your project in site mode

cd CarND-Capstone/ros
roslaunch launch/site.launch

5. Confirm that traffic light detection works on real life images