Aruco Marker Detection with OpenCV and TurtleBot3 in Gazebo

Task Overview

This task involves detecting Aruco markers in two different cases:

1. Real-world video detection: Using OpenCV to detect Aruco markers in a video recorded from a mobile camera.
2. Simulation in Gazebo: Using TurtleBot3 to detect Aruco markers in a simulated Gazebo environment.

Table of Contents

1. Prerequisites
2. Setup
3. Real-World Video Detection
4. Gazebo Simulation
5. Results
6. Images
7. References

Prerequisites

Ensure you have the following software installed:

• Python 3.x
• OpenCV
• ROS (Robot Operating System) with TurtleBot3 packages
• Gazebo
• Git

Setup

Clone the project repository:

git clone https://github.com/rishang19dx/Task_3A_Aruco_Marker_Detection.git
cd Task_3A_Aruco_Marker_Detection

Real-World Video Detection

1. Print Aruco Markers:

   • Print the provided Aruco markers on an A4 sheet.

2. Record Video:

   • Record a video of the printed Aruco markers using your mobile camera. Move the camera around to capture different angles and distances.
   • Save the video as aruco.mp4 in the project directory.
   • Add the path to the python script.

Gazebo Simulation

1. Install Required Packages:

   • Install the necessary ROS and Gazebo packages.

   • Clone the gazebo_aruco_models package from GitHub:

     git clone https://github.com/sacchinbhg/gazebo_aruco_models.git
     cd gazebo_aruco_models
     cp -r aruco_marker /path/to/your/catkin_ws/src/
     cd /path/to/your/catkin_ws
     catkin_make
     source devel/setup.bash

2. Launch Gazebo with TurtleBot3 and Aruco Markers:

   • Open Gazebo simulation in empty world and add the aruco markers using the insert tab in the Gazebo GUI

   • We shall use waffle model because it has in-built camera in it.

     export TURTLEBOT3_MODEL=waffle
     roslaunch turtlebot3_gazebo turtlebot3_empty_world.launch

Real-World Video Detection

1. Python Script:
   • Navigate to the task directory.
   • Run the provided Python script aruco.py to detect Aruco markers in the video

Gazebo Simulation

1. Launch TurtleBot3 in Gazebo:

   • Use the following command to launch the simulation:

     export TURTLEBOT3_MODEL=waffle
     roslaunch turtlebot3_gazebo turtlebot3_empty_world.launch

2. Spawn Aruco Markers:

   • Use the Gazebo GUI and add markers to the environment.

3. Run Detection Node:

   • Run the detection node to detect Aruco markers using TurtleBot3's camera:

     rosrun aruco_detection aruco_detection.py

4. View Camera Images :

   • View images from the TurtleBot3's camera topic /camera/rgb/image_raw using image_view

     rosrun image_view image_view image:=/camera/rgb/image_raw

Results

• Real-World Video Detection:

  • The script will display the video with detected Aruco markers highlighted.

• Gazebo Simulation:

  • The detection node will output the positions of the detected Aruco markers in the simulation and highlight the same in the simulation.

Images

Aruco Markers in gazebo environment

Aruco Markers Detection

References

• OpenCV Aruco Module Documentation
• TurtleBot3 Documentation
• Gazebo Aruco Models

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