This project is the localization project of the Udacity Robotics Software Engineer Nanodegree. For the project, I applied the Monte Carlo Localization (MCL) algorithm, also known as Particle Filter, in ROS to estimate the robot's own pose. See the writeup for an extended discussion of the project's theoretical content on localization and parameter tuning.
The project was developed on Ubuntu 16.04 LTS with ROS Kinetic, Gazebo and catkin installed.
The robot relies on the amcl and move_base ROS packages, which should be installed through apt-get.
Use catkin to build the packages from source. From catkin_ws, run:
catkin_make; source devel/setup.bash
to build the workspace packages and add them to the paths of ROS.
After the above steps, you should be able to run the commands below in separate terminals:
roslaunch udacity_bot udacity_world.launch
roslaunch udacity_bot amcl.launch
rosrun udacity_bot navigation_goal
The project repository contains source code of a catkin workspace, with some supporting code and shared object files provided by Udacity. All of them are wrapped in the udacity_bot package. The package includes a custom made robot model, a world file and map of an enclosed race track environment, a few configuration files for the parameters of amcl, and a node that sends a navigation goal to the robot as it starts.
There are two tasks involved in this project: robot model configuration and amcl localization.
The robot model was built through editing the urdf file in the udacity_bot package to include two wheels, a main chassis, a laser rangefinder and an RGB camera.
The robot uses the information from the odometer, the camera and the laser rangefinder to localize itself through the amcl package. However, to successfully apply the algorithm, there are many parameters to tune for the specific robot and environment. As a result, the parameter files in the config directory contains up-to-date parameters that can allow the robot to accurately localize itself. With a good estimate of its pose, the robot was able to navigate to the designated goal.
