Andreas-Jankl/CarND-Extended-Kalmanfilter

Program an EKF in C++ that can do sensor fusion for radar and lidar data

Extended Kalman Filter Project Starter Code

Self-Driving Car Engineer Nanodegree Program

This implements an Extended Kalmanfilter that is able to do a sensor fusion of given sensor readings from radar and lidar object detections.

When its being run and compared against ground truth data its px, py, vx, and vy RMSE is less than [.11, .11, 0.52, 0.52] as required for passing.

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Dependencies

• cmake >= 3.5
• All OSes: click here for installation instructions
• make >= 4.1
  • Linux: make is installed by default on most Linux distros
  • Mac: install Xcode command line tools to get make
  • Windows: Click here for installation instructions
• gcc/g++ >= 5.4
  • Linux: gcc / g++ is installed by default on most Linux distros
  • Mac: same deal as make - [install Xcode command line tools]((https://developer.apple.com/xcode/features/)
  • Windows: recommend using MinGW

Basic Build Instructions

1. Clone this repo.
2. Make a build directory: mkdir build && cd build
3. Compile: cmake .. && make
   • On windows, you may need to run: cmake .. -G "Unix Makefiles" && make
4. 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