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Udacity Self-Driving Car Nanodegree Capstone Integration Project

TEAM Renegate Robotics

  1. Alexey Makurin rufige@yandex.ru
  2. Seyfi Gozubuyuk seyfig@gmail.com
  3. Oliver Hager oli484@googlemail.com
  4. Peri Zen perizen1@gmail.com
  5. Nikolay Falaleev nikolasent@gmail.com

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.

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.

Instruction of setting up Udacity VM can be found here

IF YOU CHOOSE TO SETUP VM FROM SCRATCH (AND NOT USE UDACITY VM)

NO MATTER HOW DO YOU SETUP VM

WARN: Simulator can run on VM but it'll be extremely slow. Solution is to download version for your HOST OS (not the guest one used for VM) and setup port forwarding to VM.

Port Forwarding for Oracle VM VirtualBox

  1. First open up Oracle VM VirtualBox
  2. Click on the default session and select settings.
  3. Click on Network, and then Advanced.
  4. Click on Port Forwarding
  5. Click on the green plus, adds new port forwarding rule.
  6. Add a rule that has 4567 as both the host and guest IP.

Usage

  1. Clone the project repository
git clone https://github.com/udacity/CarND-Capstone.git
  1. Install python dependencies
cd CarND-Capstone
pip install -r requirements.txt
  1. Make and run styx
cd ros
catkin_make
source devel/setup.sh
roslaunch launch/styx.launch
  1. Run the simulator DURING 20sec after starting styx or it'll die on socket timeout

Real world testing

  1. Download training bag that was recorded on the Udacity self-driving car
  2. Unzip the file
unzip traffic_light_bag_files.zip
  1. Play the bag file
rosbag play -l traffic_light_bag_files/loop_with_traffic_light.bag
  1. Launch your project in site mode
cd CarND-Capstone/ros
roslaunch launch/site.launch

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  • Python 43.2%
  • CMake 34.0%
  • C++ 22.5%
  • Shell 0.3%