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Why Abdotonomous?
We provide a highly practical architecture for autonomous and semi-autonomous vehicles. Our system offers numerous features and can accommodate additional ones without requiring extensive manual intervention. The system supports a variety of vehicles, including electric cars, remotely operated vehicles (ROVs), autonomous underwater vehicles (AUVs), and unmanned aerial vehicles (UAVs).
Extensibility
Adding a new feature is just a piece of cake. Whenever you have a feature, implement it and add a new node to the system.
Portability
With our docker image, you can use the system anywhere regardless of the hosting platform.
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-commercial use. We are also happy to receive pull requests from you!
Features*
Info
*Adapted from Sensor Fusion Nano Degree Program
Our system boasts several advanced features, including:
- TTC Feature: This feature utilizes both camera and lidar data to evaluate the Time-to-Collision with the vehicle in front of you.
- Kalman Filter: This feature takes input data from various sensors such as lidar and radar to generate a more precise approximation of the system's quantities and localization.
- Lidar Obstacle Detection: This feature leverages Point Cloud Data (PCD) coordinates to cluster and detect obstacles surrounding the vehicle.
- GPS: Our system employs the Google Maps API (non-free) to determine the global location of your vehicle.
Technologies & Frameworks
Our system is built using the following technologies and frameworks:
- OpenCV
- C++
- Python
- ROS II
- Carla
- Docker
- Jetson Nano