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Term 2: Project 2: Unscented Kalman Filter

Sensor Fusion

Self-Driving Car Engineer Nanodegree (Udacity)

Project submission by Edward Minnett (ed@methodic.io).

March 31st 2017. (Revision 1)

Dependencies

  • cmake >= v3.5
  • make >= v4.1
  • gcc/g++ >= v5.4

Basic Build Instructions

  1. Clone this repo.
  2. Make a build directory: mkdir build && cd build
  3. Compile: cmake .. && make
  4. Run it: ./UnscentedKF path/to/input.txt path/to/output.txt. You can find some sample inputs in 'data/'.
    • eg. ./UnscentedKF ../data/sample-laser-radar-measurement-data-1.txt output.txt

Test Build Instructions

  1. Navigate to the build directory: cd build
  2. Compile (with the test set to ON): cmake -Dtest=ON .. && make
  3. Run the tests from the build directory:
    • High level over view of all test files: make test
    • Detailed execution of the tests for tools.cpp: ./ToolsTest
    • Detailed execution of the tests for ukf.cpp: ./UKFTest

Editor Settings

We've purposefully kept editor configuration files out of this repo in order to keep it as simple and environment agnostic as possible. However, we recommend using the following settings:

  • indent using spaces
  • set tab width to 2 spaces (keeps the matrices in source code aligned)

Code Style

Please stick to Google's C++ style guide as much as possible.

Generating Additional Data

This is optional!

If you'd like to generate your own radar and lidar data, see the utilities repo for Matlab scripts that can generate additional data.

Project Instructions and Rubric

This information is only accessible by people who are already enrolled in Term 2 of CarND. If you are enrolled, see the project page for instructions and the project rubric.