Extended Kalman Filter

Description

(Part of Self Driving Car Engineer program by Udacity)

Extended Kalman Filter implements a Kalman filter to track a bicycle's position and velocity in 2D using the simulated lidar and radar measurements provided by Udacity.

Documentation

Project Directory

src: The main source code directory.
data: Contains the simulated data provided by Udacity for the course.

Requirements

The project depends on Term 2 Simulator, uWebSocketIO and Eigen.

Usage

1. Clone the repository.
2. Create a directory named external
3. Place Eigen, uWebSocketIO libraries in external and proceed to create build at the root of this project. You may have to build the libraries based on your OS, platform and other variables.
4. cd build
5. cmake ..
6. make
7. You can run the project with the command ./ExtendedKF
8. The above command essentially opens a socket listening to data from Term 2 Simulator.
9. Proceed to open Term 2 Simulator and select the "EKF and UKF" option
10. You can observe the output in your console!

License

Licensed under the MIT License.