sm-azure / CarND-Extended-Kalman-Filter-Project

Self-Driving Car Nanodegree Program Starter Code for the Extended Kalman Filter Project

Extended Kalman Filter Project Writeup

Self-Driving Car Engineer Nanodegree Program

In this project you will utilize a kalman filter to estimate the state of a moving object of interest with noisy lidar and radar measurements. Passing the project requires obtaining RMSE values that are lower than the tolerance outlined in the project rubric.

This project involves the Term 2 Simulator which can be downloaded here

Rubric - Compilation

No changes have been made to the CMakeLists.txt. Simple cmake and make should be enough to compile

Accuracy

• For dataset 1, the RMSE (X,Y, VX,VY) are 0.0973, 0.0855, 0.4513, 0.4399 which is under the expected .11, .11, 0.52, 0.52 values.
• For dataset 2, the RMSE (X,Y, VX,VY) are 0.0726, 0.0967, 0.4579, 0.4966 which is under the expected .11, .11, 0.52, 0.52 values.

Algorithmic correctness and efficiency

Code has been checked for algorithmic correctness. There does not seem to be any un-necessary code either.