Extended Kalman Filter

Extended Kalman Filter Project

This project is a part of the Self-Driving Car Engineer Nanodegree Program by Udacity. In this project, an extended kalman filter is used to estimate the state of a moving object of interest with noisy lidar and radar measurements.

Setting up

Simulator

This project involves the Term 2 Simulator which can be downloaded here.

uWebSocketIO

This repository includes two files that can be used to set up and install uWebSocketIO for either Linux or Mac systems. For windows you can use either Docker, VMware, or even Windows 10 Bash on Ubuntu to install uWebSocketIO. Please see the uWebSocketIO Starter Guide page in the classroom within the EKF Project lesson for the required version and installation scripts.

Dependencies

• cmake >= 3.5
  • All OSes: click here for installation instructions
• make >= 4.1 (Linux, Mac), 3.81 (Windows)
  • 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
  • Windows: recommend using MinGW

Building the project

Once the install for uWebSocketIO is complete, the main program can be built and run using the following terminal commands from the project top directory.

1. Clone this repo.

$ git clone https://github.com/nantanitv/extended-kalman-filter/

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