Why Use Abdotonomous?

We bring out a super handy architecture for autonomous and semi-autonomous vehicles. The system provides some fancy features, yet, is capable of adding more and more without getting your hands dirty. Vehicles may be electric cars, ROVs, AUVs or UAVs.

extensibility

Extensibilty

Adding a new feature is just a piece of cake. Whenever you have a feature, implement it and add new node to the system.
Portability

Portability

With our docker image, you can use the system anywhere regardless of the hosting platform.
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Creative Commons License

Under the license of Attribution-NonCommercial 4.0 International, the source code is available and you are free to use and modify it for non-commericial use. We are also happy to recevie pull requests from you!
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Our Team

Meet our vigorous team ✨

Hagar Usama

Hagar Usama

Team Leader for phase I

Hagar planned the project's roadmap and trained the team. She implemented the lidar obstacle detection and the time-to-collision (TTC) features. Additionally, she is responsible for maintaining the GitHub organization, documentation, and this page.

Youssef Mamdouh

Youssef Mamdouh

Team Leader for phase II

Youssef designed the structure of the project consisting of various node to be as efficient as possible whilst maintaining modularity. He integrated the system, created multiple message interfaces, as well as radar data processing and Kalman filter.

Islam Mustafa

Islam Mustafa

Team Member

Islam has worked with ROS II as framework for writing the sensors' drivers. He also participated in implementing Kalman filter as a dynamic model to produce better esitmates. Besides, he participated in ROS II interfaces and ROS bridge as well.

Islam Algebaly

Islam Algebaly

Team Member

Gebaly implemented the unscented Kalman filter to identify the surrounding cars with the data coming from lidar and radar. He also integrated Kalman filter with ROS II. In addition, he participated in creating a bridge between ROS and ROS II.

Michael Ramez

Michael Ramez

Team Member

Michael implemented the GPS feature. He also participated in Kalman filter feature.

Bishoy Francis

Bishoy Francis

Team Member

Bishoy was responsible for the simulation part in Carla simulator. This includes (but not limited to) gathering synthetic data for sensors.

Abdelrahman Farag

Abdelrahman Farag

Team Member

Abdelrahman was responsible for sensors' selection and fixation. He also played a key role in selecting the machine learning framework. Unfortunately, Abdelrahman passed away during the early stages of Phase I. In honor of his contributions, the project has been named after him as a gesture of gratitude and appreciation.

Message

profile

Abdelrahman will be missed dearly. We are deeply troubled by this sudden loss. Our thoughts and prayers are with him. We are extremely sorry for his loss. Remembering him, he was always a towering pillar of virtue, a beacon whose light always guided us towards kindness and joy. We hold you close in our thoughts and hope you know that. We’ve lost a part of our team.

@Team Mixer

Available Features


TTC Feature
(Camera & Lidar)

*1
  • evaluates Time-to-Collision for the car front of you.
  • Lidar and Camera data are fused

Kalman Filer
(Lidar & Radar)

*2
  • Takes input data from different sensors such as lidar and radar
  • Produces a better approximation of the system's quantities

Lidar Obstacle Detection
(Lidar)

*3
  • Uses PCD coordinates
  • Clusters points forming the objects surrounding the car

GPS Navigation System
(GPS)

4
  • Locates your car's global location
  • Uses Google Maps API
  • non-free

Documentation