Python Library for simulating unManNed vehiclEs(PLANE) is an open source software module, written in Python, that focuses on Unmanned Aerial Vehicles (UAVs), on their movements and on the mechanics of flight, thus devoting particular attention to the equations that describe drones' movement. In the context of the Internet of Drones (IoD), the module can be widely used for the study of the mutual control of position coordination in scenarios in which drones may find obstacles, as it happens in densely populated urban scenarios. Emphasis is put on ease of use, performance evaluation, documentation, and Application Programming Interface (API) consistency. The software tool has minimal dependencies and is distributed under MIT License. Source code, binaries, and documentation can be downloaded from GitHub.
In this article we present the development of a UAV ground control station simulator. We propose a module based description of the architecture of this simulator. We recall the nonlinear model of a fixed-wing aircraft. Finally, we outline ideas for improved path planning tasks. The approach is made clear through several diagrams, figures of the resulting station are displayed. This article presents an image-based visual servoing system for indoor visual tracking of 3D moving objects by an Unmanned Aerial Vehicle. This system autonomously follows a 3D moving target object, maintaining it with a fixed distance and centered on its image plane. The initial setup is tested in a detailed simulation environment. The system is then validated on flights in indoor scenarios using the Parrot AR.Drone and the CMT tracker, demonstrating the robustness of the system to differences in object features, environmental clutter, and target trajectory. The obtained results indicate that the proposed system is suitable for complex controls task, such object surveillance and pursuit. Increasing sensing and communication capabilities combined with falling prices have made drones very attractive for Internet of Things applications. A key requirement of these applications is that the drones should be autonomously maneuvered by computer programs. It is therefore important to understand the practical limitations of autonomous drone maneuverability to ensure that target application performance is met. In this paper, we first analyze drone maneuverability using theory to shed light on the tradeoff between the flying speed and the turning agility of the drone. To investigate the practical maneuverability performance, we then emulate as well as fly a commercial drone under the control of an Android program. We reveal some practical maneuverability factors that must be considered for the applications that require frequent changes of direction for the drone.