This project is based on the template code within the scope of the localization course in Udacity Self-Driving Car Nanodegree.
A robot has been kidnapped and transported to a new location! Luckily it has a map of this location, a (noisy) GPS estimate of its initial location, and lots of (noisy) sensor and control data.
In this project a two-dimensional particle filter is implemented in C++. The particle filter will be given a map and some initial localization information (analogous to what a GPS would provide). At each time step your filter will also get observation and control data.
- Download Term 2 Simulator here and launch it.
- Install uWebSocketIO:
- This repository includes two bash files for installing uWebSocketIO on Linux or Mac systems.
- For Windows you can use either Docker, VMware, or even Windows 10 Bash on Ubuntu to install uWebSocketIO.
- Navigate to root
cd particle_filters
- Build
$ mkdir build && cd build
$ cmake .. && make
$ ./particle_filter
Alternatively, run:
$ ./clean.sh
$ ./build.sh
$ ./run.sh
.particle_filters # project root
| build.sh
| clean.sh
| CMakeLists.txt
| README.md
| run.sh
|
|___data # map data input to the filter
| | map_data.txt
|___src
| helper_functions.h
| main.cpp
| map.h
| particle_filter.cpp
| particle_filter.h
map_data.txt
has three columns [x, y, landmark_id].