joostaafjes/CarND-Capstone

Udacity Self-Driving Car Nanodegree

Capstone Project: Programming a Real Self-Driving Car

This is the final "Capstone" Project for the entire 9 month Nanodegree course.

We utilize Robot Operating System (ROS) and Autoware libraries test our code in a simulated environment

and finally get to run our code on Udacity's famous Self Driving Car "Carla".

This is our project submission and we are Team AJJAX !

Name	Email	GitHub	LinkedIn
John Reilly	johnreillymct@outlook.com	https://github.com/john-reilly	https://www.linkedin.com/in/john-reilly-ireland/
Joost Aafjes	joostaafjes@gmail.com	https://github.com/joostaafjes	https://www.linkedin.com/in/joost-aafjes-3354a4/
Xing Xing	axingdi@gmail.com	https://github.com/axingdi	https://www.linkedin.com/in/xing-xing-44260965/
Adam Gotlib	gotlib.adam@gmail.com>	https://github.com/Goldob	https://www.linkedin.com/in/adam-gotlib/

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Original Udacity README.MD below

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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

Usage

1. Clone the project repository

git clone https://github.com/udacity/CarND-Capstone.git

2. Install python dependencies

cd CarND-Capstone
pip install -r requirements.txt

3. Make and run styx

cd ros
catkin_make
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

Other library/driver information

Outside of requirements.txt, here is information on other driver/library versions used in the simulator and Carla:

Specific to these libraries, the simulator grader and Carla use the following:

	Simulator	Carla
Nvidia driver	384.130	384.130
CUDA	8.0.61	8.0.61
cuDNN	6.0.21	6.0.21
TensorRT	N/A	N/A
OpenCV	3.2.0-dev	2.4.8
OpenMP	N/A	N/A

We are working on a fix to line up the OpenCV versions between the two.