**5. 3D reconstruction of electrical infrastructure**

Effective and efficient generation of 3D models from a set of 2D images is a wellstudied problem in the literature and the principle of numerous computer vision applications. The keypoint detection and the 2D descriptor extraction are the first steps in the reconstruction process followed by the matching. There are different 2D descriptors such as SIFT, ORB, BRISK and FREAK that can be used in the context of 3D reconstruction using structure from motion (SFM). From the study [3], it can be concluded that it is possible to use the aforementioned descriptors in electrical tower reconstruction context. Also, the results shown that the SIFT descriptor presents the best performance in the generated cloud of points, but it spends more time than using other descriptors. Another good option is the use of the ORB descriptor. In **Figure 15**, a result using SIFT is presented.

Current developments tend towards the use of other types of sensors such as LIDAR whose information can be merged with information from cameras with different spectra.

Also it is important to develop an online process of object recognition by using simultaneous localization and mapping (SLAM). This can help to improve the object detection stage in order to obtain a more robust navigation system.

**Figure 15.** *Results of 3D reconstruction of electrical infrastructure.*

*Path Planning for Autonomous Vehicles - Ensuring Reliable Driverless Navigation...*

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**Figure 14.**

*Autonomous mission process stages.*

**Figure 13.** *UAV system.*

**Figure 12.**

*Simulation of autonomous navigation.*
