Unmanned aerial vehicles (UAVs) are increasingly being used in many applications due to their rapid and cost-effective deployment. UAVs are motorized aerial vehicles that do not carry a human operator, use aerodynamic forces to lift the vehicle, can fly autonomously or be piloted remotely, can be disposable or retrievable, and can carry a lethal or non-lethal payload. UAVs are a component of an unmanned aircraft system (UAS), which includes the addition of a ground controller and a communications system with the UAV. The design of a drone for a particular application includes many factors, such as the aerodynamic shape of the propellers, the strength and weight of the drone parts, the electric motor, the electric speed controller, the radio transmitter or receiver, and the software interface on the mobile phone or computer for monitoring and data analysis.
Several thrusters are provided to the drones. More propellers improve drone stability and load capacity, but these drones need more batteries to drive more motors and obtain more power. A quadrocopter is a more popular drone. The flight of unmanned aerial vehicles can operate under the remote control of a human operator, such as remotely piloted aircraft (RPA), or with varying degrees of autonomy, such as autopilot assistance, up to fully autonomous aircraft that do not have human intervention. As an auxiliary infrastructure, UAVs provide reliable wireless links for terrestrial users to carry out a secure and reliable transmission of information. With the increasing autonomy, intelligence and multitasking requirements of unmanned aerial vehicle applications, the efficiency and level of intelligence of operating a single unmanned aerial vehicle have gradually ceased to meet the requirements of the task application.
When flying alone, limited energy supply limits flight distance and operating range. At the same time, it is vulnerable to various network attacks and the reliability of communication is not high. In this context, the unmanned aerial vehicle cluster communication network comprised of multiple unmanned aerial vehicles can effectively improve the reliability of unmanned aerial vehicle communication and become the direction of development of unmanned aerial vehicle communication in the future. Route planning is very important in many real-life problems. For a mission to be successful, it is crucial to plan routes efficiently with several unmanned aerial vehicles.
Goal-oriented navigation planning is often modeled by calculating a lower-cost route from the starting location to the destination location through known or unknown environments. However, in problems with several unmanned aerial vehicles, in order to obtain an optimal solution, aerial vehicles must not only avoid collisions with obstacles, but must also avoid collisions with other unmanned aerial vehicles. Therefore, efficient and risk-free route planning is crucial for multiple unmanned aerial vehicle systems. In addition, having intermediate tasks that UAVTs must perform further increases the complexity of the problem. The malicious use of unmanned aerial vehicles has led to the development of technologies against unmanned aerial systems (C-UAS).
Unmanned aircraft systems are classified by the Army's Unmanned Aerial Systems (UAS) according to their weight, maximum altitude and speed. Unmanned aerial vehicles are used in numerous real-life applications such as payload delivery, traffic monitoring, movement of objects in seemingly hazardous environments and surveillance. UAVs are gradually being used in a wide range of real-world applications such as military operations, disaster relief and exploration of hazardous remote areas. The use of unmanned aerial vehicles is increasingly being regulated by civil aviation authorities in different countries.
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