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 @cite_5 , the authors argues that when the number of waypoints arises, together with the number of flying objects in a given area, optimization algorithm are mandatory to lower the computational overhead and the number of useless movements and or operations carried out by each drone. The rationale for the employment of multiple UAV is related to the fact that when the mission has multiple objectives, tasks differentiation among the drones in the swarm leads to increasing the efficiency of the system, while lowering the overall operational time. Therefore, it is designed a path planning algorithm for multi- UAV systems. The solution is a GA -like and foresees a number of UAV flying at constant altitude in a known environment. In the proposed solution, once the GA routine has found a feasible solution, it is smoothed using Bezier curves. This visionary proposal still has some margins of enhancements since it does not address kinetic problems such as minimum curvature and or torsion and maximum climb angle.
@cite_5
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Unmanned Aerial Vehicles (UAVs) are used in numerous military and civil application areas, and they have gained prominence in the research community. A UAV has to operate in a complex environment and checks the control points in the mission area by satisfying different constraints of the assigned task. Therefore, the path planning problem is one of the important areas in UAV researches. If the number of control points increases in the Unmanned Aerial System (UAS), finding a feasible solution in this large search space takes up a great deal of time. Nowadays low-cost UAVs are available, and this enables the use of multi-UAV systems to perform different tasks more efficiently and quickly. This usage increases the complexity of effective path planning and task allocation problem. This paper presents a flyable path planning for multi-UAV systems by using a Genetic Algorithm (GA) in a known environment at a constant altitude. A feasible path is firstly calculated by GAs, and then this path is smoothed by using Bezier curves. Experimental results indicate that the proposed approach produces effective and feasible paths for each UAV in a multi-UAV system. System is implemented in Java with a GUI for presenting results. The paper also draws future works that can be done on this topic.