Abstract
The rapid advancement of unmanned aerial vehicles (UAVs), commonly known as drones, has opened up new possibilities for various applications, including aerial imaging, surveillance, delivery services, search and rescue operations. One particular area of interest is the integration of computer vision techniques with drones to enable autonomous detection and recognition of visual markers or codes. The objective of this research is to design and implement an efficient and accurate QR code detection system using the Tello drone. Our project aimed to develop a solution that only requires a simple vision system to achieve accurate positioning (altitude) in closed spaces. The method is developed in python environment using OpenCV library. This paper presents an efficient method for QR code detection using HSV color space algorithm. Based on experiments and findings, it is recommended to maintain a range of approximately 90cm - 120cm for optimal QR code reading using the Tello drone. This range provides a suitable balance between capturing clear and detailed images of the QR codes and ensuring accurate decoding and recognition. The combination of the Tello drone and computer vision techniques provides an efficient and reliable solution for QR code detection in practical scenarios. Lastly, this research also able to stimulate further innovation in the field and inspire the development of more sophisticated and efficient QR code detection systems using autonomous drones.