patrick-woo / term2-p2-carnd-ukf

Unscented Kalman Filter

This Project is the seventh task (Project 2 of Term 2) of the Udacity Self-Driving Car Nanodegree program.

The main goal of the project is to apply Unscented Kalman Filter to fuse data from LIDAR and Radar sensors of a self driving car using C++.

The UKF is used to the CTRV model.

Content of this repo

• scr a directory with the project code:
  • main.cpp - reads in data, calls a function to run the Unscented Kalman filter, calls a function to calculate RMSE
  • ukf.h - head file for the ukf.cpp to define the variables and functions.
  • ukf.cpp - initializes the filter, calls the predict function, calls the update function
  • tools.h- defines the functions and variables of tools.cpp
  • tools.cpp - a function to calculate RMSE
• README.md the Readme for the UKF udacity project

Result

Accuracy - RMSE: [0.06, 0.08, 0.33, 0.21]

Threshold: RMSE <= [.09, .10, .40, .30]

Accuracy - RMSE: [0.06, 0.06, 0.61, 0.27]

Threshold: RMSE <= [.09, .10, .40, .30]

How to run the code

Clone this repo and perform

mkdir build && cd build
cmake ..
sudo make
./UnscentedKF