joustava / SensorFusion_P5

C++ project which is a solution to the Extended Kalman Filter project of Udacity's Self Driving Car Engineer Nano Degree

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Extended Kalman Filter

Self-Driving Car Engineer Nanodegree Program Project 5

In this project a kalman filter is utilised to estimate the state of a moving object of interest with noisy lidar and radar measurements. Passing the project requires obtaining RMSE values that are lower than the tolerance outlined in the project rubric.

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

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.

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

This code can be build an run on a Mac provided that the Mac setup from the course material has been followed.

The code can also be run in Linux (Archlinux), this to prove it builds at least on Mac and Linux.

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C++ project which is a solution to the Extended Kalman Filter project of Udacity's Self Driving Car Engineer Nano Degree

License:MIT License


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