# Framework for Fast Experimental Testing of Autonomous Navigation Algorithms
## 6 Experiments
### GNSS/SLAM Fusion Framework Experiments
#### 6.4.2 Autonomous Navigation  
In the previous section, we described the experiments carried out to test the localization but in that case, the control loop closure was being performed by the users who handle the remote control. Because of this, we are influencing the localization by using our own human localization at the cognitive level. In order to test how location affects control, we integrated into our vehicle the architecture shown in Figure 3 to navigate autonomously in closed circuit. Using the paths recorded during the previous experiments we generated two maps of trajectories through the routes \(R3\) and \(R4\) (Section 6.4.1), defining two different circuits. For these experiments, the application is configured to run through the specified circuit indefinitely. In this way, we will be able to observe the repetitiveness of the trajectories in each lap. With these conditions, we carried out four different experiments. First, we performed the autonomous navigation along the circuit defined by the path \(R3\) using the GNSS in standalone mode. Next, we used the circuit described by the path \(R4\) also with the GNSS configured  
Figure 16: Trajectories through the \(R3\) path expressed by localization using the fusion described in Section 5. (**left**) Using GNSS standalone. (**right**) Using GNSS floating point. We see that in the case of the fusion with GNSS real-time kinematic RTK floating point (**right**), in the off-map area the fusion adapts to these observations.  
Figure 17: Trajectories through the \(R4\) path expressed by localization using the fusion described in Section 5. (**left**) Using GNSS standalone. (**right**) Using GNSS floating point. In this case, the whole area \(x>50\) m is off-map. We see that in both cases we can make the re-entry on the map. However, in the case of the GNSS RTK floating point (**right**) the trajectory seems more consistent except in the curve located in the lower right quadrant, where conditions were very unfavorable due to occlusions and multi-path produced by trees and buildings.  
in standalone mode. In order to see how the differential corrections of GNSS can affect navigation, we repeated the two experiments previously described but using the RTK in floating mode.  
The system behavior in the paths \(R3\) and \(R4\) with the standalone GNSS configuration was similar. In both cases, the errors of the standalone GNSS system caused failures in the zones marked with yellow circles in Figure 18. These errors resulted in emergency stops, thanks to the system described in Section 4.2.4. However, it was possible to demonstrate the system recoverability since, after skipping these areas in manual driving we were able to complete the circuit autonomously. During the RTK experiments, the system was able to complete the circuit without interruptions including the off-map areas. The behavior in these experiments was very similar to the described in the previous section: the system shown repeatability and a smooth and stable control without oscillations. However, in these experiments we were not able to circulate indefinitely, since in the second lap, in the areas marked with yellow circles in Figure 18 we lost connection with the base station, disabling the RTK mode and forcing to interrupt the autonomous navigation. As in the previous case, the system proved to be recoverable as it returned to autonomous navigation after passing these critical points.