In today’s world, UAVs commonly known as drones are being used in so many areas such as inspection, surveying, mapping, agriculture, mining, public safety, construction, security, unmanned cargo, science and research. For example, UAVs can be used for mapping the areas like civilian areas to observe people or crop fields to explore them. Also, there are so many usage areas of UAVs in daily life. For example, nowadays, in so many movie set, UAVs are using as flying cameras. Despite the fact that UAVs are used in so many areas, the way that UAVs are used is quite a bit restricted. If the UAV is controlled manually by a human, visual surveillance is required all the time to use the UAV. Also, there are some restrictions for autonomous flight of UAVs.
An unmanned aerial vehicle (UAV) is an aircraft that can be controlled remotely by a human or fly autonomously by onboard computers. The most extensive definition of UAV is that: “A powered, aerial vehicle that does not carry a human operator, uses aerodynamic forces to provide vehicle lift, can fly autonomously or be piloted remotely, can be expendable or recoverable, and can carry a lethal or nonlethal payload.” [1]. Unmanned aerial vehicles are a part of an unmanned aircraft system (UAS). UAS contains a UAV, a ground-based controller, and a system of communications to connect the UAV and the controller [2]. If we want to categorize UAVs, this categorization should be based on control and autonomy; because the most important question about UAVs is that what are the UAVs autonomous control levels. Level 1 represents remotely guided control and level 10 represents fully autonomous control [3].
Recently, autonomous UAVs take place as so many manned operations in remote control and they are so popular for different kinds of lightweight deliveries. The computing systems for UAVs are becoming a new research field in cyber-physical systems. Autonomous UAVs require integrated intelligent decision making systems to control and manage their flight missions when no human operators exist. There are some crucial characteristic properties of UAVs for their mission control and management systems [4]. First property is collision avoidance. Second one is GPS coordinates for UAVs navigation method. Third one is optimization of battery lifetime. Fourth and the last property is UAV’s own features such is its velocity, position and attitude.
Collision avoidance is very significant requirement for autonomous UAVs. The UAV system should have the capacity to plan and re-plan, if it is necessary, its own flight. This results in the requirement for a high level computing environment where flight algorithms can be run. The flight planning operation requires knowledge of the UAV’s environment; including airspace, land, weather, restricted areas, obstacles and other UAV traffics. The UAV must plan the optimal route for its mission path according to local environment, flight time and fuel usage. If anything happens, the UAV must have the capacity to do the essential configurations and re-plan its mission path [5].
The UAV should be design with a GPS tracking system and programmed to be able to fly autonomously from one location to another with the use of GPS tracking system coordinates. Also, safety and toughness due to the possibility of collision with different kind of objects should be considered [6]. Environmental conditions are also very important to use UAVs. UAVs are expected to travel in high altitudes according to the way they invented. They are highly sensitive vehicles to wind and other weather conditions. These kind of extremely dynamic conditions should be considered in a real time manner. For example, if we consider the effect of the wind, this is a real concern for the flight of UAVs [4].
Ordinary UAVs are powered by onboard batteries with limited capacity but UAVs are expected to carry out long missions. A fully autonomous UAV management system that can optimize the operations of battery lifetime to extend their operation time is highly desirable for today’s technology. Many UAVs are only convenient for short distance uses, that’s why their applicability is restricted. To optimize the battery performance of UAVs, it is important to know their state of charge and optimize the operations accordingly [4].
Position, velocity, and attitude are also known as the navigation states of UAV. The sensors used to measure these quantities are called navigation sensors: an inertial measurement unit (IMU) and global positioning system (GPS) receiver [7]. Operational requirements for these kinds of UAVs typically include flying close to the ground and in relatively narrow spaces with a lot of obstacles. This introduces problems for a simple application of technologies used in larger UAVs. In particular, the rotary wing UAV platforms used in those scenarios provide vertical take-off and landing and hovering capability, but they are originally unstable systems requiring high-rate and accurate attitude and position data to be automatically controlled [8].
In summary, unmanned aerial vehicles commonly known as drones have some characteristic properties such as collision avoidance, GPS coordinates for UAVs navigation method and optimization of battery lifetime. Our project aims at developing navigation algorithms for autonomous drones. The project will be based on using visual maps describing indoor and outdoor environments. In addition, the evaluation measurements, and obstacle avoidance will be based on information from virtual sensors. The implementation will be in a simulation environment [9].