# Multi-Sensor Fusion for Aerial Robots in Industrial GNSS-Denied Environments
## 4 Conclusions  
Based on the results, it can be concluded that the algorithm fulfills its goals in terms of accuracy and computational efficiency. The proposed multi-sensor fusion approach provides a good trade-off, allowing variation of the proportional weight between the use of the different available sensor modalities. As for the UWB sensors, it is necessary to emphasize that the more sensors there are in the environment, the better the accuracy of the pose estimation; however, this would involve infrastructure maintenance issues for a permanent localization solution in any given scenario. It may be of interest to the scientific community to try to locate the UAV without indicating an initial starting point. However, aerial robots perform rapidly changing movements thanks to their 6 degrees of freedom. This means that when the algorithm tries to locate the robot in a certain position, it is already in a different one. There are \"jumps\" in the estimation of the robot's position that cause the algorithm to not converge correctly. Therefore, this type of algorithm is not prepared for the first initialization step to be performed automatically; that is, it is necessary to enter an initial position so that the convergence is adequate in real time and the pose of the aerial robot can be correctly estimated. Even though technological equipment has greatly advanced in recent years and allows the processing of units with higher computational capabilities, aerial robots' payload is still a limiting factor that needs to be addressed when it comes to onboard real-time computations. Further research directions involve the use of additional sensors in the particle filter, such as a laser altimeter to keep the height estimation errors bounded, which are critical for the safe operation of aerial robots. Furthermore, additional improvements can be addressed within the algorithm, such as a more efficient resampling method. Nevertheless, the proposed method has been validated in a realistic indoor scenario as a suitable localization algorithm for the localization of aerial robots in GNSS-denied environments. Figure 11: Flight of [25]. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**X—Axis (m)** & **Y—Axis (m)** & **Z—Axis (m)** & **Yaw (Degree)** \\ \hline
0.36 & 0.39 & 0.17 & 10.313 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: RMS errors with MCL [25]. **Author Contributions:** Conceptualization, F.J.P.-G.; Data curation, P.C. ; Funding acquisition, A.V. ; Investigation, P.C., F.C. and R.C. ; Methodology, F.C. ; Project administration, F.J.P.-G. and A.V. ; Software, P.C., F.C. and R.C. ; Supervision, F.C. and F.J.P.-G.; Validation, P.C. ; Writing--original draft, P.C. All authors have read and agreed to the published version of the manuscript. **Funding:** This work was partially funded by ROSIN, a European Union H2020 project, under grant agreement no. 732287, the DURABLE project (financed by Interreg Atlantic Area Programme through the ERDF from the EC), and the PILOTING H2020 project, under grant agreement no. 871542. **Institutional Review Board Statement:** Not applicable. **Informed Consent Statement:** Not applicable. **Data Availability Statement:** Publicly available datasets were analyzed in this study. This data can be found here:[[https://github.com/fada-catec/amcl3d/releases](https://github.com/fada-catec/amcl3d/releases)]([https://github.com/fada-catec/amcl3d/releases](https://github.com/fada-catec/amcl3d/releases)) (accessed on 26 April 2021). **Conflicts of Interest:** The authors declare no conflict of interest. **Sample Availability:** The ROS package is avaliable at [[https://github.com/fada-catec/amcl3d](https://github.com/fada-catec/amcl3d)]([https://github.com/fada-catec/amcl3d](https://github.com/fada-catec/amcl3d)) (accessed on 26 April 2021), with corresponding documentation at [[http://wiki.ros.org/amcl3d](http://wiki.ros.org/amcl3d)]([http://wiki.ros.org/amcl3d](http://wiki.ros.org/amcl3d)) (accessed on 26 April 2021).