Self-Driving Car Engineer Nanodegree Program
This project implements a sensor fusion scheme for lidar and radar data. It uses the kalman filter and extended Kalman filter for laser and radar measurements respetively.
The exteneded Kalman filter is used in the radar data because transfer function for the radar is not linear.
This is how the information is processed:
Please (do your best to) stick to Google's C++ style guide.
(Click for interactive visualization)
(Click for interactive visualization)
- cmake >= 3.5
- make >= 4.1
- gcc/g++ >= 5.4
- Clone this repo.
- Make a build directory:
mkdir build && cd build
- Compile:
cmake .. && make
- Run it:
./ExtendedKF path/to/input.txt path/to/output.txt
. You can find some sample inputs in 'data/'.- eg.
./ExtendedKF ../data/sample-laser-radar-measurement-data-1.txt output.txt
- eg.
Note: regardless of the changes you make, your project must be buildable using cmake and make!
- You don't have to follow this directory structure, but if you do, your work will span all of the .cpp files here. Keep an eye out for TODOs.
https://eigen.tuxfamily.org/dox/group__TutorialMatrixClass.html
http://www.cs.unc.edu/~tracker/media/pdf/SIGGRAPH2001_CoursePack_08.pdf
http://www.cs.unc.edu/~welch/kalman/media/pdf/maybeck_ch1.pdf
Introduction to Random Signals and Applied Kalman Filtering with Matlab( Robert Brown)