This ROS node is designed to track and visualize the movement of a ball in real-time using computer vision techniques. The node captures video from a camera source (usually the default webcam, but you can change the source by modifying the cv2.VideoCapture parameter) and processes the frames to detect and track the ball.
Before running this ROS node, make sure you have the following dependencies installed:
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ROS 2: This code is written for ROS 2 (Robot Operating System 2). You must have a ROS 2 installation on your system. Follow the ROS 2 installation instructions for your operating system here.
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OpenCV: This code relies on the OpenCV library for computer vision tasks. You can install OpenCV for Python using pip:
pip install opencv-python
To run the node, follow these steps:
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Clone or download this repository to your ROS 2 workspace.
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Build your ROS 2 workspace to compile the node:
colcon build -
Source your ROS 2 workspace:
source install/setup.bash -
Run the ROS 2 node:
ros2 run <your_package_name> <your_node_name>Replace
<your_package_name>and<your_node_name>with the appropriate package and node names in your ROS 2 workspace. -
The node will start capturing video from the camera and display it in a window. It will detect and track circles (presumed to be a ball) in the video stream. The coordinates of the detected ball's center (normalized) will be displayed on the video frame.
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Press the 'q' key to exit the program.
You can customize the behavior of the ball tracking by modifying the parameters in the tracker method of the MyNode class. Here are some important parameters you can adjust:
minDist: Minimum distance between the centers of detected circles.param1andparam2: Parameters for circle detection using the Hough Circle Transform.minRadiusandmaxRadius: Minimum and maximum radii of the circles to be detected.