Extended Kalman Filter Project Starter Code

Self-Driving Car Engineer Nanodegree Program

In this project, an extended kalman filter is utilized to estimate the state of a moving object of interest with noisy lidar and radar measurements. The program has been tested against the data set in /data/obj_pose-laser-radar-synthetic-input.txt, and yield the overall RMSE within [.11, .11, 0.52, 0.52] related to error in position coordinate and velocity.

This repository includes two files that can be used to set up and install uWebSocketIO for either Linux or Mac systems.

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

1. mkdir build
2. cd build
3. cmake ..
4. make
5. ./ExtendedKF

Tips for setting up your environment can be found in the classroom lesson for this project.

The computation and pipeline of kalman filter is in files : src/FusionEKF.cpp, src/FusionEKF.h, kalman_filter.cpp, kalman_filter.h, tools.cpp, and tools.h

main.cpp mainly uses for uWebSocketIO in communicating with the simulator as parsing the data files.

INPUT: values provided by the simulator to the c++ program

["sensor_measurement"] => the measurement that the simulator observed (either lidar or radar)

OUTPUT: values provided by the c++ program to the simulator

["estimate_x"] <= kalman filter estimated position x

["estimate_y"] <= kalman filter estimated position y

["rmse_x"]

["rmse_y"]

["rmse_vx"]

["rmse_vy"]

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Other Important 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

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