The goal of this thesis is to develop a solution for controlling a drone by using body gestures. We developed the solution in the form of a mobile application for Android devices. We used a Tello drone, produced by the company Ryze Robotics. This drone offers a network interface for receiving commands. It also has a built-in camera for capturing a video feed, which can be streamed to a connected device. Our implementation is structured as a closed loop, which contains three consecutive phases or modules. These are image decoding, pose estimation and gesture classification. Based on the results of the gesture classifier, a command is defined and issued to the drone. We evaluated the analyzed system by measuring latencies across modules of the loop and also by using empirical methods on actual examples of controlling the drone with gestures. We demonstrated, that our is able to function properly in practice. At the end we expose current issues of our solution and suggest possible improvements. The first group of issues occur because of ambiguities in the input images. These can be resolved by preprocessing the image. The other issues are related to the gesture classifiers architecture, which is not optimal for our problem.