Real-Time Tracking and Distance Measurement of Opencv Aruco Marker Using Webcam

Object tracking and distance measurement play a vital role in robotics and drones. It is often challenging to measure the distance of a target object in an environment by just using a single-vision camera. This paper discusses the development of a fiducial marker-based object tracking and distance measurement system. Fiducial marker detection uses the ArUco method based on the OpenCV library and Python 3.x. The hardware consists of an Arduino, a single-vision camera, and two servos as an actuator for tracking. A mathematical equation is derived to measure the real-time distance of the marker by using a single camera and adjusting the frame size and the camera output colors to increase the detection method’s performance. OpenCV is used to find the center coordinates of the bounding box, and a tracking algorithm is applied to give pan/tilt angles to the servos. Finally, to stabilize the tracking mechanism, an acceptable error is defined. The accuracy of the system is measured by performing 100 trials, and the results show a good accuracy for the system when tracking the ArUco marker. The system is highly beneficial for indoor mobile robot navigation and drone applications

OpenCV, Fiducial marker, Python, Computer vision, Robotics, Aruco marker.

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