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Project: Gazebo Integration using API

Project Status: WIP – Initial development is in progress, but there has not yet been a stable, usable release suitable for the public.


Concepts Used

Following are the concepts used for this project:

  • ROSlaunch API
    • To import the image using path
    • To import the image using camera
    • To set thresholds for Canny edge detection
  • ROS tf
    • To set the values of threshold parameters
    • To fetch the values of threshold parameters

Directory Structure

  • Following is the directory structure of the package
    ├── CMakeLists.txt
    ├── docs                             # README dependencies
    │   ├── tf.png
    │   └── tree.txt
    ├── include
    │   └── TurtleSim-tf
    ├── launch                           # Launch files
    │   ├── dynamic.launch                 # Launch - Multiple instance of same node using launch file
    │   └── spawn.launch                   # Launch - Multiple turtles in a turtlesim using launch file
    ├── nodes                            # ROS Nodes
    │   ├──                   # Blueprint of a node - spawn random turtles and broadcast transform
    │   ├──                    # Launch multiple instances using ROSlaunch API
    │   └──                      # Turtle class to control turtle activities
    ├── package.xml
    └── src

Coding Style Guide - PEP8


  • ROS-tf2 package
  • turtlesim package

Setup and Run

To run the project on your local system, follow the procedure:

  • Download the packages - turtlesim-tf

  • Copy these packages to your ROS workspace i.e. ~/ROS_ws/src/

  • Build the work-space

    • $ cd ~/ROS_ws/
    • $ catkin_make

Using XML

File associated - dynamic.launch and

Using Python Script

File associated - and

  • Open new terminal and source the ROS workspace - source ~/ROS_ws/devel/setup.bash

  • Run the command - $ roslaunch turtlesim-tf xxxxxx.launch 5

    • where 5 = number of turtle in a turtlesim

      You can configure this number

  • In a new terminal, run the command - $ rqt_tf_tree to display the tf-tree

  • This is an architecture for Gazebo
  • There are two main nodes - server and a client
  • Server handles all the physics, sensors and calculation part
  • Client's job is to render all this data in the simulator
  • Gazebo's server and client keeps communicating continuously
  • After reading the data from this communication channel, we can read sensor data, simulation data and the physics data
  • This data once augmented with ROS arguments can be sent over ROS topics to be accessed by the ROS nodes



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