Submission for Project 3 of Udacity Robotics Nanodegree: Implement Adaptive Monte Carlo Localisation (AMCL) algorithm to localise a robot in a pre-generated map. Particle position and orientation are shown as blue arrows in RViz - as the robot localises in the environment, the number of particles will reduce to a single arrow indicating the localised pose.
This project is intended to be built within a catkin workspace. To build, clone this repo into the catkin_ws/src folder and run catkin_make.
- Add existing .yaml map file of the Gazebo environment in
my_robot/maps:- Recommend to follow the instructions in https://github.com/udacity/pgm_map_creator for a static map.
After sourcing setup.bash (if not already in .bashrc):
$ roslaunch my_robot world.launch
$ roslaunch my_robot amcl.launch
