# 3D Path Planning Algorithms in UAV-Enabled Communications Systems: A Mapping Study
## 2 Background
### 3D Path Planning
Energy consumption comprises three primary components: flying energy, which represents the energy expended by the UAV during its journey from the starting point to the destination; floating energy, which denotes the energy necessary for the UAV to stay airborne and fulfill its assigned task; and transmission energy, which refers to the energy utilized by the UAV for data transmission back to the source. For UAV path planning to be implemented successfully, some aspects must be considered, such as the environment of the place where it will fly. The size of the area, the obstacles encountered during the flight, the quantity of UAVs involved in the mission, and the approach taken by the UAV in route planning are all crucial factors in path planning. These aspects will be further elaborated below [18]. * **Number of UAVs:** A mission can be carried out by one or several UAVs. The number of UAVs used will depend a lot on the type of application that will be developed, such as in a drone-controlled light show where several UAVs will require a well-defined path planning to avoid collisions and achieve the desired effect [20]. * **Obstacles:** Any object that interrupts the flight of the UAV is considered as an obstacle, it is for this reason that the path planning must be focused on detecting obstacles, avoiding these obstacles and guaranteeing its way to the destination. Obstacles can be classified as technical, which are the restrictions developed to successfully and economically complete a task. On the other hand, non-technical obstacles can be static limitations, such as buildings, mountains, trees, or dynamic limitations that become unexpected threats, such as a bird. To avoid both dynamic and static obstacles, the UAV may be equipping the UAV with sensors that allow it to detect obstacles at all times. Likewise, another way to avoid collisions is to define restricted flight areas [1]. * **Environment:** The environment can be uncertain as it frequently changes from static to dynamic. For this reason, the environment in which the UAV must fly must be known, and the path planning in uncertain environments. Several studies have been carried out in different habitats implementing different algorithms that can solve the complexity of an uncertain environment [1]. * **Altitude:** Three-dimensional path planning is somewhat complex because the altitude constantly changes, which causes the UAV to have to change its speed and direction frequently [1]. * **Distance:** This aspect is focused on the distance of the path planning. Online path planning is performed in real-time, and the environmental conditions must be considered while the UAV is heading to its destination. Offline path planning instead is developed before the UAV begins its flight. In this case, there is information about the terrain and obstacles where the UAV will develop its flight [1]. Figure 3 shows the environment of a city where a UAV must plan the best possible route to complete its mission. For this purpose, the UAV must know the area's dimensions, obstacles that may arise during the flight, and the city's environmental conditions. All these aspects are vital when planning an optimal path.