## 1 Introduction  
Over the past decade commercial drones, and quadcopters in particular, have become increasingly popular and affordable. In addition to their use in professional or casual photography, they have grown into a transformative force in diverse sectors, including inspection [1, 2], mapping [3, 4], exploration [5], human-machine interaction [6], search-and-rescue missions [7, 8], and more. More recently, their combination with virtual and augmented reality (VR and AR, respectively) has yielded new experiences such as first-person-view (FPV) lights (www.dji.com/gr/dij-fpv, accessed on 20 December 2021), AR training (vrscout.com/news/drones-training-drone-pilots-with-ar/, accessed on 20 December 2021), and mixed reality games (www.dji.com/newsroom/news/edgybees-launches-the-first-augmented-reality-game-for-dji-drone-users, accessed on 20 December 2021). Learning to pilot a quadcopter effectively can be a challenging task: Conventional remote controllers are largely unintuitive, as they use two joysticks to control flight, with one corresponding to horizontal motions (pitch and roll) and the other to vertical (throttle) and rotational (yaw) motions. Additional wheels and buttons control the drone's camera. While basic motions in relaxed circumstances are achievable with short training sessions, complex motions can be more difficult. Moreover, in challenging or stressful circumstances (e.g., in disaster response or under tight time constraints), the lack of intuitive controls add additional cognitive load on the pilot, affecting his/her safety and efficiency. In addition,the remote controller in itself, requiring the continuous use of both hands, can be restrictive. Although alternative remote controllers, such as the DJI motion controller, provide a less cumbersome solution, they cannot support the full range of motions executable by a traditional remote. Another challenge stems from the difference in position and orientation between the drone and its pilot, which can make it difficult to match the drone's camera feed with the pilot's surroundings. In particular, especially when the drone is at some distance or out of direct line of sight, it can be challenging both to judge its position and orientation and have a direct understanding of where its camera is pointing at. Moreover, as the video feed is normally displayed on a screen attached to the remote, it requires users to constantly change their focus from the drone (in the air) to the screen (usually held at chest level, hence towards the ground), glancing from one to the other. This can be both tiring (mentally as well as visually) and adds to the cognitive load, as the user alternates between two different points of view. Although VR FPV mode eliminates the change of perspective, it leaves users unaware of their own surroundings, which can be prohibitive in many cases. In this paper, we propose an AR solution that leverages gesture recognition, computer vision AI, and motion tracking techniques to provide a natural user interface for intuitive drone control and contextualized information visualization. Based on the Microsoft HoloLens 2 headset ([[https://www.microsoft.com/en-us/hololens/hardware](https://www.microsoft.com/en-us/hololens/hardware)]([https://www.microsoft.com/en-us/hololens/hardware](https://www.microsoft.com/en-us/hololens/hardware)), accessed on 20 December 2021), the presented system allows users to pilot a drone using single-hand gestures, improves tracking the position of the drone in an AR environment, and provides video feed visualization in either the contextualized or FPV modes. It allows for a comfortable flight, as both hands are free and can be used for other tasks when not directing the drone. AR tracking improves drone visibility in longer distances or in low light conditions. The visualization of the drone's video feed in the AR display means that users can view both the video and their surroundings without glancing towards different directions.