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Title:

Cube Pose Tracking using OpenCV and ArUco Board in ROS

Overview Video

Overview

This ROS (Robot Operating System) node implements ArUco marker detection and pose estimation for a cube in a camera's field of view. It subscribes to camera information and image topics, performs marker detection using OpenCV's ArUco library, and estimates the pose of a cube with ArUco markers. The resulting pose information is published as a PoseStamped message and visualized using RViz markers.

Prerequisites

  • ROS installed
  • OpenCV installed (cv2, cv2.aruco)
  • tf library installed
  • numpy library installed

Usage

  1. Clone this repository into your ROS workspace.

    git clone https://github.com/ammar-n-abbas/aruco-cube-pose-tracking-ros.git

  2. Build the ROS workspace.

    cd path/to/your/ros/workspace
catkin_make

  3. Run the ROS node.

    rosrun your_package_name aruco_cube_pose.py

ROS Topics

  • Subscribed Topics:

    • /camera/color/camera_info (CameraInfo): Camera information topic.
    • /camera/color/image_raw (Image): Raw camera image topic.

  • Published Topics:

    • /aruco_cube/pose (PoseStamped): Pose of the detected cube.
    • /visualization_marker_real_cube (Marker): RViz visualization marker for the cube.

Parameters

  • Marker Size: The size of the ArUco marker used for detection.
  • Cube Size: The size of the cube.

Notes

  • The node assumes a specific marker dictionary (DICT_6X6_1000). Please ensure that this matches your setup.
  • Marker visualization in RViz is represented by a cube.