# Development of Path Planning Tool for Unmanned System Considering Energy Consumption
## 5 Simulation and Experimental Setups
### Experiment Setup  
All experiments were performed with the parts shown in Figure 1--a PX4 Pro powered F450 quadrotor, shown in Figure 10a; Pixhawk 2.1 flight controller, as in Figure 10b; QGroundControl (QGC), shown in Figure 10c; Pixhawk 2.1 Here + RTK, as in Figure 10d; eLogger V4 voltage and current data logging system, as shown in Figure 10e; and a 4s 3300-mAh battery pack, shown in Figure 10f--for the outdoor autopilot experiment with a previously achieved energy-efficient path. In particular, the Pixhawk 2.1 Here + RTK is used for the centimeter-level autopilot path following accuracy.  
The overall experiment setup is presented in Figure 11. On the day of the experiment, the wind speed was approximately 2 m/s.  
For the experiment, the SPP and EEPP trajectories represented as the Cartesian system unit, \(Trajectory_{xyz}\), obtained from the path-planning algorithm shown in Figure 2 are converted into the geographic coordinate system unit, \(Trajectory_{GPS}\). The detailed description can be found in previous work [24].  
In particular, the waypoint list of \(Trajectory_{GPS}\) is saved as a text file following the Pixhawk waypoint file format, as depicted in Table 1[25]. For the waypoints lists of SPP and EEPP trajectories, see Appendix B.  
Figure 10: Flight experiment parts: (**a**) F450 quadrotor, (**b**) Pixhawk 2.1, (**c**) QGroundControl (QGC), (**d**) Pixhawk 2.1 Here+ RTK, (**e**) eLogger V4, and (**f**) 4s 3300-mAh battery pack.  
Energy consumption comparison results of the SPP and EEPP algorithms are listed in Table 2 and Figure 13.  
The percentage difference between the actual values of SPP and EEPP is shown in Table 3 and Figure 14. According to the result, the SOC leftover is larger and the SOP peak is lower when using SPP.  
The percentage difference between the actual values of SPP and EEPP is shown in Table 5 and Figure 17. According to the result, the SOC leftover is larger and the SOP peak is lower when using EEPP.  
The overall reference, simulation, and experiment flight trajectories of the SPP and EEPP algorithms are drawn on Google Earth, as shown in Figure 18. Here, yellow polygons represent imaginary obstacles that the UAV should avoid. The blue line represents the reference trajectory that the UAV should follow. The red line represents the simulation flight trajectory. The green line represents the experiment flight trajectory.  
Figure 16: SOC and SOP comparison (experiment): (**a**) SOC and (**b**) SOP.  
Figure 17: The comparison results in percentage (experiment).  
\begin{table}
\begin{tabular}{l c} \hline \hline  &
\begin{tabular}{c} \(\text{\text{\text{\text{SPP}}}-EEPP}\)**\(\times\)100 (\%)** \\ \end{tabular} \\ \hline Total Trajectory Distance (m) & \(-5.47\) \\ Min. Speed of UAV (m/s) & \(0\) \\ Max. Speed of UAV (m/s) & \(-9.76\) \\ Weight of UAV (kg) & \(0\) \\ Total UEC (Wh) & \(6.68\) \\ Algorithm Run Time (s) & \(-76.72\) \\ SOC Leftover (\%) & \(-0.96\) \\ SOP Peak (W) & \(-11.03\) \\ \hline \hline \end{tabular}
\end{table}
Table 5: Comparison result in percentage (experiment).