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ros

Simple projects in Robot Operating System (ROS).

ROS is an open-source system used for programming robots. In this project you can find various packages implemented for an autonomous robot, specifically the Turtlebot (the Turtlebot2 was used in this project, which could be easily adapted for the Turtlebot3).

What can I find here?

Note that Gazebo is used in all the packages for the world and the robot simulation (with an exception of Intro to ROS). The communication with it is achieved through the topic /cmd_vel (for publishing commands) and through the topics /odom and /kobuki/laser/scan (for collecting information).

Intro to ROS

Firstly, you can find a very simple example with 4 types of ROS Nodes in the package sensors. The 4 types are:

  • Publisher
  • Subscriber
  • Service
  • Action

The way these nodes communicate is shown in the picture below. The node /measurement gets and publishes the data from the sensors, while the node /processing processes it and sends it further on.

Movement control

The robot movement control is implemented in the package kinematics, where you could find the controllers for both manual and autonomous movement.

To communicate with the controller just type in the mode you would like to use ('manual' or 'auto'), followed by a manually given velocity command (for manual mode) or the target position (for auto mode). Below you can find an example of the robot position before and after the commands sent by an user have been executed.
Robot's initial position () and target position ()

Obstacles detection

An obstacles detection is implemented in the package perception. Split and Merge algorithm is applied to the data retrived from the laser scan (through the topic /kobuki/laser/scan). This data is further used for extracting the lines of the walls.

If you ran Rviz in parallel, you could see the laser scan and visualized walls. On the following image(s) you can see the current position of a in the world, and all the detected walls visualized in Rviz.
Robot's position in the world Detected walls, visualized in Rviz

Kalman Filter

Kalman Filter Localization is implemented in the package kalman. The implementation is based on the Autonomous Mobile Robots Course from ETH Zurich.

Note that this package depends on the laser line extraction from this repo.

How to run these scripts?

To run any script, simply type in the following command(s) in a terminal:

  roscore # Type this only before running the very first script.
  rosrun <package> <script.py>

You can run any top-level script from the packages: sensors, kinematics and perception.

Note that if you wanted to perform a world and a robot simulation you should have Gazebo. Therefore, before running the aforementioned scripts you should run Gazebo by typing in the following command(s) in a terminal:

  roslaunch turtlebot_gazebo turtlebot_world.launch

If you want to visualize obstacles detected by the laser scan, simply type in the following command(a) in a terminal, in order to run Rviz. After that, add the topics /kobuki/laser/scan and /visualization_marker_array.

  roslaunch turtlebot_rviz_launchers view_navigation.launch

Have fun!