Development of software for contactless control of UAVs

Abstract

The article is devoted to the development of a program for contactless control of a UAV using a neural network that tracks the position of an object. For these purposes, a corresponding model was trained on the ultralytics YOLOv8 neural network. The graphs of the training of this model are presented, demonstrating the change in the magnitude of the loss function over the bounding box and class, as well as the values of the mAP50-95 metric. The training was completed when the value of the mAP50-95 metric was 0.855. Software has been developed to control the UAV using hand movements, its block diagram and description are given. The program reads the coordinates of the hand in each frame, calculates its area, evaluates the received data and sends control commands to the copter, which moves in the appropriate direction for a given step, including a certain group of LEDs. At the same time, the screen displays a simulation of the drone›s movement in two projections (front and top) and displays the relative coordinates of the drone. The software was tested on a Geoscan pioneer mini quadcopter. It can be used for educational, demonstration purposes, in agriculture, UAV sports competitions, aerial photography and video filming and other fields of activity.