# 3D Path Planning Algorithms in UAV-Enabled Communications Systems: A Mapping Study
## 4 Results
### RQ2--Are There Optimal Methods for Path Planning in 3D UAVs? RQ2 seeks to provide data on the different variables to be optimized for path planning in 3D. Table 8 shows the variables that researchers have considered optimizing by applying different path-planning techniques. Among these are the flight altitude of the UAV, the inclination angle of the UAV to rise, collision avoidance of the UAV, air density where the UAV is going to fly, the distance between the starting point of the UAV and its target, evasion of radars in restricted places, exploration and exploitation of the best routes, power of the UAVs to fulfill the mission, constant angular velocity Q to lengthen the duration of its energy. Distance and altitude are the variables that the researchers most considered. Due to the complexity of 3D path planning, the altitude is constantly changing, which causes the UAV to have to change its speed and direction frequently. In this regard, Table 9 also shows the optimization variables related to each contribution analyzed. This table shows that, of the 37 contributions analyzed, 32.43% (12) of the papers have multiple variables to be optimized. For instance, in paper A-11, the researchers optimize altitude, collisions, distance, radar evasion, and power. Instead, in paper A-17, the researchers optimize the altitude and the angle of inclination for the elevation of the UAV. In papers A-02, A-03, A-05, A-07, A-08, A-16, A-18, A-25, and A-26, there are two variables to optimize, of which the altitude of UAV flight is the dominant one. The rest of the articles only have one variable to optimize. Figure 14 shows the papers vs. the variables to be optimized, where the lead-colored bars indicate the number of articles that have worked with multiple variables. \begin{table}
\begin{tabular}{c c} \hline
**UAVs** & **Total** \\ \hline Multiple & 17 \\ \hline Single & 20 \\ \hline \end{tabular}
\end{table} 
Table 7: Types of obstacles that researchers consider for path planning. \begin{table}
\begin{tabular}{c c} \hline
**Optimized Variables** & **Total** \\ \hline Altitude & 21 \\ \hline Tilt angle & 1 \\ \hline Collisions & 1 \\ \hline Air density & 1 \\ \hline Distance & 26 \\ \hline Evade Radars & 1 \\ \hline Exploration and exploitation & 1 \\ \hline power & 1 \\ \hline Angular velocity Q & 1 \\ \hline \end{tabular}
\end{table} 
Table 8: Variables that the researchers optimized in their investigations. \begin{table}
\begin{tabular}{c c c} \hline
**Obstacles** & **Types** & **Total** \\ \hline \multirow{2}{*}{Non Technicians} & Dynamic & 6 \\ \cline{2-3}  & Static & 29 \\ \hline Technicians & Economic & 2 \\ \hline \end{tabular}
\end{table} 
Table 9: Types of obstacles that researchers consider for path planning. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**ID** & **Altitude** & \begin{tabular}{c} **Inclination** \\ **Angle** \\ \end{tabular} & **Collisions** & **Air Density** & **Distance** & **Evade Radars** & \
\begin{tabular}{c} **Exploration/** \\ **Explitation** \\ \end{tabular} & **Power** &
\begin{tabular}{c} **Angular** \\ **Velocity Q** \\ \end{tabular} & **Multiple** \\ \hline A-01 & x & & & x & & & & & x \\ \hline A-02 & x & & x & & & & & x \\ \hline A-03 & x & & & x & & & & x \\ \hline A-04 & & & & x & & & & \\ \hline A-05 & x & & & x & & & & x \\ \hline A-06 & & & & x & & & & x \\ \hline A-07 & x & & & x & & & x \\ \hline A-08 & x & & & x & & & x \\ \hline A-09 & x & & & & & & & x \\ \hline A-10 & x & & x & x & x & x & x \\ \hline A-11 & x & x & x & x & x & x & x \\ \hline A-12 & & & x & & & & \\ \hline A-13 & x & & & & & & \\ \hline A-14 & x & & & & & & \\ \hline A-15 & x & & & & & & x \\ \hline A-16 & x & & x & & & x \\ \hline A-17 & x & x & & & x & x \\ \hline A-18 & x & & x & & & x \\ \hline A-19 & & & & x & & & \\ \hline A-20 & & & x & & & \\ \hline A-21 & & & x & & & \\ \hline A-22 & & & x & & & \\ \hline A-23 & & & x & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Optimization variables of each contributions analyzed.