# Autonomous 3D Exploration of Large Structures Using an UAV Equipped with a 2D LIDAR
## 6 Results and Discussion
### Flight Path  
To illustrate the progression of the structure exploration throughout a run, Figure 16 shows the evolution of the occupied space. A snapshot was taken at the end of the initial manoeuvre and every 30 min after that. The first two snapshots show the most significant change in occupied space. By comparing Figure 16d with Figure 17a,b the characteristics of each heuristic are visible. The nearest neighbour and the octomap heuristic resulted in similar pat  
Figure 16: The evolution of occupied space present, throughout a mission cycle. A snapshot is taken at the end of the initial manoeuvre and every 30 min after that. The last snapshot shows the final map. The light blue line illustrates the path taken by the vehicle. The white outline represents the search space defined by the operator. Figure 15: The volume explored at the end of the run for each of the analysed heuristics. Both **(a)** the total explored volume and **(b)** the volume of occupied space. The scales of the explored volume is one order of magnitude higher than the amount of occupied space, consequently **(b)** magnifies the difference of the outcome of each heuristic. The surface frontier heuristic circled the towers and kept to that side of the scenario. With all heuristics, the path entered the open gates. Figure 17(a) shows the path travelled by the UAV in one of the runs scaled with the map generated by the sensor data collected throughout the path. Each area of the map was visited only once, shortening the length of the flight path. As the flight progressed, the map also progressed towards completion. Figure 17: A comparison of the final map with different heuristics. The path is represented as a white line. The search space is represented as a white box. The measurements are incorporated into the world representation even if they are outside the navigational bounds defined by the operator. (**a**) Nearest neighbour and (**b**) surface frontier. The flight path adjusted to the available free space allowing the system to sample heterogeneous shapes. This flexibility allowed for a transition from outdoor to indoor inspection seamlessly, provided that there was enough connecting free space. In Figure 19, the segment of the path started above and outside a building and continued inside. The safety distance was maintained from the walls and the opening. In Figure 19a, there were visible parts of the ceiling that were unknown, but after sampling in (b), the ceiling was fully mapped. The UAV took advantage of the range of the Hokuyo sensor mounted with a 50\({}^{\circ}\) pitch to gather information because of the 270\({}^{\circ}\) scan angle, which generated a blind angle that faced downwards. Finally, the path is analysed in the light of the criteria for coverage planning, as defined by [PERSON] et al. [58]:  
* The final flight plans could cover an average of 92% of the search space. However, instead of an area, this is now the target volume;  
Figure 19: (**a**) Exploration transitions between indoors and outdoors seamlessly. The starting point is below. The target is represented by the unknown point above in dark blue. The yellow spheres represent the safety margin around each point. The required safe flight corridor in each segment has the same diameter. The purple cubes are the voxels containing each waypoint. The different sizes show the sparse quality of the octree. (**b**) The same detail viewed from inside the structure. Figure 18: (**a**) Flight path with 507.3 m. (**b**) The flight plan adapts to the features of the structure. * The region was filled out without overlapping paths;
* The paths were continuous and sequential without any repetition, although its execution was not continuous in time.