What is FOO Cars?

This autonomous vehicle project's goal is to create autonomous racing vehicles in the simplest possible way—a good first car. The name is a mash-up of Fubar Labs, the mysterious planes called "foo fighters" and "foobar" the ubiquitous getting started variables for programming. The control system can scale to any vehicles using RC controls.

How has this project been used?

• CHI@Edge 2022 Summer Internship
• Virtual exercises to access the Cameras, Serial Devices, GPIO Devices, and Machine Learning Environments
• CHI@Edge 2021 Summer Internship
  • Virtualize the deployment of vehicle and code on the edge of super computer envrionment.

FUBAR Labs Autonomous Racing Vehicles

Autonmous Vehicle Project at Fubar Labs for the Autonomous Powerwheels Racing compeition.

• Bergen Technical Highschool Workshop Spring 2023
• Bergen Technical Highschool Workshop Spring 2021
• Autonomous Powerwheels Racing Pittsburg Makerfiare 2017
• We totally did laps. We were on the track on time and ready to go!
• Autonmous Powerwheels Racing Makerfaire NYC 2017
• Autonmous Vehicle Competition via Sparkfun at Denver Makerfaire 2017

Quickstart

Car Code

Prepare your PI

Obtain the car code by cloning the project

git clone https://github.com/fubarlabs/foocars

For the Tensorflow 1.15 version fetch the wheel file to the local system:

cd ~/foocars
sh get_tensorflow.sh

Install system packages

sudo apt-get  install build-essential cmake pkg-config libjpeg-dev libtiff5-dev libjasper-dev libpng-dev libavcodec-dev libavformat-dev libswscale-dev libv4l-dev libxvidcore-dev libx264-dev libfontconfig1-dev libcairo2-dev libgdk-pixbuf2.0-dev libpango1.0-dev libgtk2.0-dev libgtk-3-dev libatlas-base-dev gfortran libhdf5-dev libhdf5-serial-dev libhdf5-103 libqtgui4 libqtwebkit4 libqt4-test python3-pyqt5

Install poetry

sudo pip3 install poetry

Install platformio

sudo pip3 install platformio

Use poetry to create the generate the car

cd ~/foocars/cargenerator
poetry install
poety run generatecar --name yourhostname --output_dir /home/pi/foocars/cars/

Use poetry to create the car code and service

cd ~/foocars/cars/carservices
poetry install

Test the PI Hat

poetry run test_pihat

Test the Car Runner

poetry run car_runner

Verify the leds and switches are working.

Pepare the RC Car and Arduino

Note for Arduino

Code is installed from the Raspberry PI using PLatform IO

sudo pip3 install platformio

Teensy 3.2 Code

cd ./cars/templatecar/arduino/teensy-FullAutoDrive-port

Arduino Code

pio run -t upload

Finish the PI set up

Set up the raspberry pi services

cd /etc/systemd/system/
sudo ln -s ~/foocars/cars/carservices/carservices/car.service 
sudo systemctl start car
tail -f /var/log/syslog

Verify the car service is running the car runner

Training code

Find a system with a good gpu. It was slow but worked on a Raspberry PI 4.

cd ~/foocars/training

poetry install
poetry shell

The training command:

Using TensorFlow backend.
usage: train.py [-h] [--weight_filename WEIGHT_FILENAME]
                [--init_weights INIT_WEIGHTS] [--delay DELAY]
                [--epochs EPOCHS] [--save_frequency SAVE_FREQUENCY]
                directories [directories ...]

Run the training:

python train.py --epochs 100 --save_frequency 2 ../cars/youcar/data/collected

Alternately use this example Google Colab Notebook

• FooCars Training: https://colab.research.google.com/drive/1LxZyNQvWT2VasnOrNkU9dTcpo4B9I0aD?usp=sharing

2023 Training with Docker

https://colab.research.google.com/drive/1oT3M4QVUoNYkFh4pzktVNBfT0zULwSpM?usp=sharing