Udacity Robotic Software NanoDegree

Where Am I Project

Introduction

The main objective of this project is to learn to utilize the ROS AMCL(Adaptive Monte Carlo Localisation) package to accurately localize a mobile robot inside a map in the Gazebo simulation environment.and To learn several aspects of robotic software engineering with a focus on ROS:

*Create a ROS package that launches a custom robot model in a custom Gazebo world

*Utilize the ROS AMCL package and the Tele-Operation / Navigation Stack to localize the robot

*Explore, add, and tune specific parameters corresponding to each package to achieve the best possible localization results

Motivation

To consolidate the robotic concepts learned in the Udacity Robotics Nanodegree and get a hands-on experience of working with C++, ROS, Gazebo simulation enviroment.

Prerequisites and Dependencies

1.Install Gazebo>=7.0 and ROS kinetic in Linux.

2. Cmake>=3.0 and gcc/g++>=5.4

3.ROS Navigation Package

  sudo apt-get install ros-kinetic-navigation

4.ROS map_server package

   sudo apt-get install ros-kinetic-map-server 

5.ROS move_base package

   sudo apt-get install ros-kinetic-move-base

6.ROS amcl package

   sudo apt-get install ros-kinetic-amcl

Build and Run the project

1.Clone and Intialize the catkin workspace.

   $ mkdir -p catkin_ws
   $ cd catkin_ws/
   $ git clone https://github.com/RamCharanThota/Udacity_Robotic_ND_Proj3_WhereAmI.git src
   $ cd catkin_ws/src
   $ catkin_init_workspace 

2. Build the packages.

 $ cd ../
 $ catkin_make

3. launch robot and world in Gazebo simulation environment.

$ source devel/setup.bash
$ roslaunch my_robot world.launch 

4. launch amcl node

 $ source devel/setup.bash
 $ roslaunch my_robot amcl.launch

5.Drive and Localise

  You can control or drive  the robot two ways while it localize itself here:
  *control through RViz by using navigation goal
  *control through teleop package where you can drive robot using
  your key board. 

6.Test and Tune

   while you drive the robot arround you will observe the AMCL node localisation in action. you can tune AMCL node parameters to improve the performace of the algorithm.