# Coverage Path Planning with Semantic Segmentation for UAV in PV Plants
## 3 Results and Discussion
### Discussion  
The proposed strategy allows a semi-automatic and faster solution for achieving effective results when inspecting PV plants in geometrically simple areas, with certain limitations, although some results obtained in this work are theoretical results, such as from CPP width, for example; in practice, a camera of 14 megapixels is not adequate to inspect a PV plant with a CPP width of 20 m [37; 101]. The results obtained in this work indicate that the most adequate method is BECD for a specific range of CPP widths, although it also shows adequate performance for various CPP widths in some RoIs. The GBWC showed a good performance when using a CPP width greater than 7 m in some RoIs, and all showed a relationship with the area to be covered, as shown in Tables 1 and 2. An analysis of the metrics used in this work, such as redundancy, \(R_{\%}\), which does not represent a significant factor when comparing these three CPP methods, showed that, although the BECD was the method with the highest redundancy, it was also the method with the lowest consumption of energy. On the other hand, the other metrics, such as the \(L_{ct}\) metric, flight time metric, and the number of maneuvers, are directly related to energy consumption, as can be seen in Appendix B and C. It also helps to conclude that the BECD method is more suitable for widths in a range between 0 and 7 m, due to the lower number of maneuvers in these ranges, as other authors have also mentioned [102; 103]. The percentage of coverage of the total area, \(C_{\%}\), always showed that coverage was total  
The \(L_{ct}\) metric, flight time and number of maneuvers were directly related to the consumption of energy for all the experiments performed, as seen in Figures 9-11 and 13-15, and as confirmed by other authors [89; 90], in addition to helping to reinforce that the most appropriate CPP for certain ranges is the BECD. The BECD method is the best method among the three methods tested, in a specific width range, from 0 to 7 m, for all the RoIs tested, which means that for a 10 Megapixel camera with a horizontal field of view of 7 m, the CCP method's good images, in terms of what to inspect of a PV plant can be obtained [23]. Figure 16: Performance test of UAV 3 DR Iris varying the CPP width. The implemented BECD method divided the RoI into small regions, and then, over these regions, it implemented the round-trip coverage pattern, called boustrophedon [38; 39]. This pattern allows spending less energy consumption with small widths, due to its low number of maneuvers compared with the other methods, as shown in Appendix B and C.  
On the other hand, the GBWC method allowed lower energy consumption, according to the results of the simulations, in widths greater than a certain value, but depending on RoI size; this method also allows an approximate coverage outside the RoI, a characteristic that is very important in this type of application, and that, perhaps, is not very attractive for terrestrial robotics, from which this type of method originates [86]. A RoI with many concave points is a great challenge for performance metrics, since they increase with the distance of travel, and also increase the number of maneuvers and therefore increase energy consumption, according to these results in the following works [67; 103], a more detailed analysis on these characteristics was made. In future works, the methods (BECD, GBWC) could be implemented in UAVs with characteristics similar to those used in this work; these characteristics are shown in Tables A1 and A5. Additionally, with these UAVs, an inspection could be conducted in at least one PV plant. Where one can think about the implementation of an expert system that selects the coverage path between the two types of methods (BECD, GBWC), according to the CPP width size, required for a camera with a certain resolution, and focal length. Finally, the results obtained with the BECD, and GBWC methods differ from the results obtained by other authors [34; 35; 36; 37].