# Developing and Field Testing Path Planning for Robotic Aquaculture Water Quality Monitoring
## 4 Results
### Issues  
A number of hardware and software failures were experienced during the automated flight tests. Because the SplashDrone does not have an absolute above-sea-level altitude estimate, it is designed to reach a desired altitude relative to the takeoff location. This causes issues when the elevation of the ponds are significantly different because the drone will reach inconsistent altitudes when traveling between the ponds. This is not only a problem for airspace deconfliction, but it requires that the drone's altitude be set according to the maximum difference in elevation of its ponds. This is not ideal from a battery or safety perspective, and supports the use of a flight controller which can be programmed to take off to a specified sea level altitude, or the use of an altitude tracking device such as a downward facing lidar. This way, the drones can be assigned to certain altitudes to avoid the possibility of in-air collisions. Using an above-ground-level altitude assigned may also work and reduce the amount of altitude required to keep airspace deconflicted, but introduces greater complexity as the drones would be changing altitude between ponds.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Method** & **Drone 1** & **Drone 2** & **Drone 3** & **Total** & **Average** \\ \hline GLOP & 23 & 26 & 28 & 77 & 26 \\ GAM & 29 & 24 & 25 & 78 & 26 \\ HPP & 37 & 19 & 37 & 93 & 31 \\ \hline \hline \end{tabular}
\end{table}
Table 10: Battery Drain (%).  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Method** & **Drone 1** & **Drone 2** & **Drone 3** & **Total** & **Average** \\ \hline GLOP & 586 & 621 & 448 & 1655 & 552 \\ GAM & 689 & 517 & 586 & 1792 & 597 \\ HPP & 863 & 426 & 862 & 2151 & 717 \\ \hline \hline \end{tabular}
\end{table}
Table 8: Flight Time (seconds).  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Method** & **Drone 1** & **Drone 2** & **Drone 3** & **Total** & **Average** \\ \hline GLOP & 1518 & 1716 & 1848 & 5082 & 1694 \\ GAM & 1914 & 1584 & 1650 & 5148 & 1716 \\ HPP & 2442 & 1254 & 2442 & 6138 & 2046 \\ \hline \hline \end{tabular}
\end{table}
Table 9: Battery Drain (mAh).  
Toward the end of our testing, one of the drones experienced a water leak during a pond landing and was subsequently damaged. This is a critical concern for HAUCS, as the drones will be expected to work robustly without leaks. This particular drone had crashed earlier during testing, so the damage from that crash likely caused a fault in a seal or a crack in the body. Future iterations of HAUCS will require great care in the design of the drone body to ensure the testability of a watertight seal in the event of a crash and as a matter of regular maintenance. It is worth mentioning that the HAUCS payload design is platform-neutral and can be easily integrated into other drones.  
Another failure occurred which resulted in the drone directing itself off course and into the tree line, which was likely caused by a glitch of the onboard GPS. Though high accuracy GPS is not required, the GPS-based navigation needs to be reliable and fault-tolerant, especially due to the risk of crashing during automated flights. Better design of the flight controller may be required to address such an issue. The SplashDrone did not provide much useful data in flight logs, making certain issues difficult to troubleshoot. Object avoidance measures such as radar or vision would also be a possible solution, as supported in the open-source flight control software Ardupilot.