Extended Kalman Filter

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An implementation of kalman filter for predicting and tracking the position and velocity of a moving object in a 2D world. The tracking is done using the input from two sensors:

• Laser (LIDAR)
• RADAR

The LIDAR sensor measures only the position of the object. The RADAR sensor provides measurement for the range (radial distance $$\rho$$ from the origin), bearing (angle between x-axis and the range vector and also the radial velocity (change of $$\rho$$).

In this project, we use the Kalman Filter (KF) to combine the measurements from these two sensor to predict a 4D state of the moving object that includes its position and its velocity.

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/obj_pose-laser-radar-synthetic-input.txt