Start with the runlocalization track.m which is

the entrance function to your lab. This function reads two les determined by

simoutle and maple input arguments which contain information about sensor

readings and the map of the environment respectively, runs a loop for all the

sensor readings and calls the ekf localize.m to perform one iteration of EKF

localization on the readings and plots the estimation(red)/ground truth(green)

and odometry(blue) information.-This lab consists of two parts:

1. A preparatory case study with a standard Kalman lter where you learn

more about the behavior of the Kalman lter. Very little extra code is

needed.

2. The main lab 1 problem in which you need to complete an implementation

of an Extended Kalman lter based robot localization.