Robot Navigation Using SLAM-ROS

This Repository will explain my 2nd task in Robotics and AI department at SMART METHODS summer training.

Task Requirements:

• Use Turtlebot3 (ROS standard platform robot) with SLAM approach (simultaneous localization and mapping) to creat a map using Lidar sensor and then save the map.

Detailed Steps:

1. we start this task, I installed Ubuntu 18.04 and ROS Melodic with Gazebo and Rviz Simulator (see my repo). Now, I will Install ROS 1 on Remote PC using the following comand

   • sudo apt update
   • sudo apt upgrade
   • wget https://raw.githubusercontent.com/ROBOTIS-GIT/robotis_tools/master/install_ros_melodic.sh
   • chmod 755 ./install_ros_melodic.sh
   • bash ./install_ros_melodic.sh

2. Install Dependent ROS 1 Packages

   • sudo apt-get install ros-melodic-joy ros-melodic-teleop-twist-joy \ ros-melodic-teleop-twist-keyboard ros-melodic-laser-proc \ ros-melodic-rgbd-launch ros-melodic-depthimage-to-laserscan \ ros-melodic-rosserial-arduino ros-melodic-rosserial-python \ ros-melodic-rosserial-server ros-melodic-rosserial-client \ ros-melodic-rosserial-msgs ros-melodic-amcl ros-melodic-map-server \ ros-melodic-move-base ros-melodic-urdf ros-melodic-xacro \ ros-melodic-compressed-image-transport ros-melodic-rqt* \ ros-melodic-gmapping ros-melodic-navigation ros-melodic-interactive-markers

3. Install TurtleBot3 Packages

   • sudo apt-get install ros-melodic-dynamixel-sdk
   • sudo apt-get install ros-melodic-turtlebot3-msgs
   • sudo apt-get install ros-melodic-turtlebot3

4. Install Simulation Package where the TurtleBot3 Simulation Package requires turtlebot3 and turtlebot3_msgs packages as prerequisite. Without these prerequisite packages, the Simulation cannot be launched.

   • cd ~/catkin_ws/src/
   • git clone -b melodic-devel https://github.com/ROBOTIS-GIT/turtlebot3_simulations.git
   • cd ~/catkin_ws && catkin_make
   • Then write cd or open new terminal and write source ~/catkin_ws/devel/setup.bash or use echo "source ~/catkin_ws/devel/setup.bash" >> ~/.bashrc

5. Launch Simulation World.There are 3 simulation environments are prepared for TurtleBot3 and I will lunch one by one just for testing (we can choose one of them later).

• Empty world with a robot called "burger"

  • export TURTLEBOT3_MODEL=burger
  • roslaunch turtlebot3_gazebo turtlebot3_empty_world.launch

  

• TurtleBot3 World with a robot called "waffle"

  • export TURTLEBOT3_MODEL=waffle
  • roslaunch turtlebot3_gazebo turtlebot3_world.launch

  

• TurtleBot3 House with a robot called waffle_pi

  • export TURTLEBOT3_MODEL=waffle_pi
  • roslaunch turtlebot3_gazebo turtlebot3_house.launch

  

6. We will choose one of the previous robot which is waffle and we weill cintrol it usit the keybored keys W: Forward, A: Left, S:Stop, D: Right, X:Backward. So, Run the previous comand for waffle robot then open new terminal and run the following command:
   • roslaunch turtlebot3_teleop turtlebot3_teleop_key.launch

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7. Now, close everthing and lets use SLAM simulation to creat the a map for our world, and then save the map with help of lidar sensor. There are 3 Gazebo environments are prepared as mentioned in step 5, but for creating a map with SLAM, it is recommended to use either TurtleBot3 World or TurtleBot3 House. So, I will use TurtleBot3 World with a robot called "waffle" to creat the map and save it.

   • Lunch the Gazebo environment with waffle robot export TURTLEBOT3_MODEL=waffle then roslaunch turtlebot3_gazebo turtlebot3_world.launch

   • Open new terminel to Run SLAM Node export TURTLEBOT3_MODEL=waffle then roslaunch turtlebot3_slam turtlebot3_slam.launch slam_methods:=gmapping

   • Open a new terminal to control the waffel robot and scan the area using lidar sensor export TURTLEBOT3_MODEL=waffle then roslaunch turtlebot3_teleop turtlebot3_teleop_key.launch. (in the terminal we will control the robot direction using W,A,S,D,X keybored keys).

   

8. When the map is created successfully in Rviz, open new terminal and save it using the command rosrun map_server map_saver -f ~/map

   

9. Task is Done 😍