ArUco ROS Noetic - USB Cam Detection with Calibration

This repository contains a setup for detecting ArUco markers using the aruco_ros package with ROS Noetic, a USB webcam, and Docker for easy deployment and testing.

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📷 Camera Calibration

Before running the ArUco detection node, you must calibrate your camera to obtain the correct intrinsic parameters.

Steps:

1. Open and run the Jupyter Notebook:

notebooks/camera_calibration.ipynb

This notebook will guide you through capturing calibration images and generating the camera intrinsic parameters.

2. After calibration, save the resulting YAML file to:

camera_calibration/my_webcam.yaml

The ArUco detection node will load this file at runtime to correct lens distortion and compute accurate poses.

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▶️ Running the Docker Container and Testing the ArUco Detection Node

All necessary build and run commands are provided in:

cmd.txt

This file includes:

• Docker image build instructions
• Docker container run commands
• ROS launch command for the ArUco detection node

By following these commands, you can launch the entire system inside Docker and test ArUco detection using your webcam.

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🧱 Install Dependencies Locally (Without Docker)

If you prefer to run the project on your local system instead of using Docker, follow these steps to install all required dependencies on a machine with ROS Noetic installed (Ubuntu 20.04):

1. Update and Install System Packages

sudo apt update
sudo apt install -y \
  ros-noetic-ros-base \
  ros-noetic-usb-cam \
  ros-noetic-rqt-image-view \
  ros-noetic-rqt-graph \
  ros-noetic-rqt-topic \
  ros-noetic-rviz \
  python3-rosdep \
  python3-colcon-common-extensions \
  python3-catkin-tools \
  python3-pip \
  git \
  build-essential

2. Initialize and Update rosdep

sudo rosdep init
rosdep update

3. Create and Configure a Catkin Workspace

mkdir -p ~/ros_ws/src
cd ~/ros_ws/src

4. Clone the Required Packages

git clone https://github.com/pal-robotics/aruco_ros.git
cd aruco_ros
git checkout noetic-devel
cd ~/ros_ws

5. Install Package Dependencies

rosdep install --from-paths src --ignore-src -r -y

6. Build the Workspace

source /opt/ros/noetic/setup.bash
catkin build

7. Source the Workspace

Add this to your ~/.bashrc to automatically source your workspace every time:

echo "source ~/ros_ws/devel/setup.bash" >> ~/.bashrc
source ~/.bashrc

8. Add Calibration File

Copy your camera calibration file (e.g., my_webcam.yaml) into the workspace:

mkdir -p ~/ros_ws/calibrations
cp camera_calibration/my_webcam.yaml ~/ros_ws/calibrations/

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🧱 Project Structure

.
├── camera_calibration/
│   └── my_webcam.yaml              # Camera intrinsic parameters (after calibration)
├── camera_calibration.ipynb    # Jupyter Notebook for camera calibration
├── Dockerfile                  # Docker setup for ROS Noetic and aruco_ros
├── launch/
│   └── usb_cam_aruco.launch        # Launch file to start webcam and ArUco detection node
├── cmd.txt                         # Build and run commands for Docker and ROS
└── ...

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✅ Requirements

• Docker installed
• USB webcam connected
• Printed or displayed ArUco markers (for detection testing)

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✅ Usage Flow

1. Calibrate your camera → Save results to camera_calibration/my_webcam.yaml
2. Build and run the Docker container → Follow steps in cmd.txt
3. Launch the ArUco detection node → Using the provided launch file
4. Point your webcam at an ArUco marker and observe detection results (it can be seen through rqt_image_view in the aruco_marker_publisher/result topic)

The results are published to /aruco_marker_publisher/markers, like this:

header: 
  seq: 0
  stamp: 
    secs: 1751980672
    nsecs: 969804506
  frame_id: "usb_cam"
id: 115
pose: 
  pose: 
    position: 
      x: -0.00266
      y:  0.01967
      z:  0.44075
    orientation: 
      x: 0.98798
      y: -0.01915
      z: 0.02042
      w: -0.15197
  covariance: [ ... ]

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✅ Notes

• Accurate calibration significantly improves detection stability and pose estimation.
• Displaying markers on computer screens may cause detection issues due to flickering, anti-aliasing, or poor viewing angles. Printed markers are recommended for better results.

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