## 5 Experiments
### Hybrid Localization Concept Verification  
The main part of the experiments was verification of the proposed concept using a BLE-based localization system and laser ranging sensors. The test was conducted in a typical, fully furnished flat, which was the flat modeled in the simulations. As in simulations, the experiment consisted of walking along two test paths and localizing the user using BLE-based and hybrid algorithms. Localization results were compared with the results obtained using a TDOA-based UWB positioning system developed at WUT during one of the earlier projects [10]. The layout of the apartment and places where the infrastructure elements were placed is presented in Figure 11.  
Figure 10: Measured FoV of VL53L1X. The infrastructure used in the experiment comprised two parts: BLE positioning system and ranging sensors. The positioning system consisted of nine BLE anchors fixed to the walls and one tag worn by the user. All of the devices were equipped with Laird BLE652 modules, which were programmed to broadcast five BLE packets per second. The received results were averaged per second to mitigate signal power fluctuations. The tag was worn on a lanyard. As the proximity sensors P-NUCLEO-53L1A1 modules including VL53L1X sensors were used. The modules were placed at the height of 1.4 m, so that the beam was directed at person's corpus. Ranging rate was set to 10 Hz, and the obtained distances were averaged per second to match BLE part localization rate. The UWB-based localization system used as reference consisted of nine anchors, which were placed in the same places as the BLE-based infrastructure. In the system, the user was localized three times per second using an EKF-based algorithm utilizing TDOA measurement results [10]. The experiment consisted of walking along two test paths. In the first experiment, the user visited room 1, room 3 and the kitchen, where he stood in front of the stove for a few seconds. The second path included rooms 2 and 3 and the bathroom, where the user spent a few seconds in the shower cabin. The collected measurement results were used to localize the user with the algorithms described in Section 3. The algorithms used were: EKF using only BLE RSS results, loosely coupled hybrid algorithm and tightly coupled hybrid algorithm. The results for both paths are presented in Figures 12 and 13. Figure 11: Layout of BLE system infrastructure and laser sensors used in the experiment for: (a) test path 1, (b) test path 2. The obtained localization results are similar to those calculated during the simulations. In case of all tested solutions, the system's accuracy is significantly lower in the border rooms, where most of the transmission occurs in NLOS conditions. It can especially be seen in the kitchen, where the user location estimated with both BLE and UWB based systems is outside the flat. Using ranging sensors in the kitchen allowed to localize the user in front of the stove. It did not have much effect in the living room, where the visualized path was still away from the reference. There were no significant differences in the results obtained using both algorithms. Figure 12: Experiment results obtained for test path 1 using: (**a**) loosely coupled hybrid algorithm, (**b**) tightly coupled hybrid algorithm with BLE-based localization results as reference. Figure 13: Experiment results obtained for test path 2 using: (**a**) loosely coupled hybrid algorithm, (**b**) tightly coupled hybrid algorithm with BLE-based localization results as reference. For the second path, similar observations can be made. Using ranging sensors, visibly improved positioning accuracy in the bathroom and room number 2. The user is localized directly in the shower cabin, which was difficult using solely BLE (but was achieved using UWB). Additionally, the results are aligned close to the reference trajectory in room 2. Covering room 4 with one ranging sensor did not work very well. Since it was a single sensor and the covered area was small, there was no significant improvement in the accuracy.