Implementation of Extended Kalman Filter for state estimation & localization using odometry data and LIDAR input
The vehicle motion model recieves linear and angular velocity odometry readings as inputs, and outputs the state (i.e., the 2D pose) of the vehicle.
The measurement model relates the current pose of the vehicle to the LIDAR range and bearing measurements
Note Refer the jupyter notebook for more details
