State Estimation and Localization for Self-Driving Cars

Run

Refer the source code (ipynb file).

Algorithm Used

Error-State Extended Kalman Filter (ES-EKF)

• Algorithm is implemented using Python3 programming language.
• Dataset containing measurements from a sensor array involving IMU, a GNSS receiver, and a LiDAR on a moving self-driving car is used for the development of the Kalmna filter.
• A reasonable estimate of the vehicle's pose and velocity is derived using sensor fusion and compared with ground truth data from the CARLA simulator.

Results