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.
- CHI@Edge 2021 Summer Internship
- Virtualize the deployment of vehicle and code on the edge of super computer envrionment.
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
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.
Code is installed from the Raspberry PI using PLatform IO
sudo pip3 install platformio
cd ./cars/templatecar/arduino/teensy-FullAutoDrive-port
pio run -t upload
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
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
- FooCars Training: https://colab.research.google.com/drive/1LxZyNQvWT2VasnOrNkU9dTcpo4B9I0aD?usp=sharing
https://colab.research.google.com/drive/1oT3M4QVUoNYkFh4pzktVNBfT0zULwSpM?usp=sharing