Self-driving Car Nanodegree Project 1/Term 2 - Appplying a Kalman Filter to estimate the state of a moving object with lidar and radar measurements. Passing the project requires obtaining RMSE values that are lower that 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 this concept in the classroom 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.
- mkdir build
- cd build
- cmake ..
- make
- ./ExtendedKF
-
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
For Dataset 1, the RMSE for the output coordinates for each frame is here and the final RMSE for the coordinates are represented on the image below.
