# Autonomous Loading System for Load-Haul-Dump (LHD) Machines Used in Underground Mining
## 5 Conclusions  
A complete autonomous loading system for LHD machines for underground mining was presented. The loading system considers identification of the rock pile, positioning of the machine in front of it, charging against the rock pile, excavating, moving away from the draw point, and estimating the bucket weight or fill factor. Despite that the proposed system was fully implemented (including the necessity for a human operator to be involved in the process in order to complete the task when the system fails), it could not be tested as a whole. The proposed system which implements the whole loading process, the excavation algorithm, and the tests in a real production environment are the most important contributions of this work. The experimentation phase was divided between onsite execution and validation of the excavation algorithm, and offline data processing for the rock pile identification method. In the onsite experiments, identification and positioning were bypassed in favor of teleoperation by a human operator. It was also the operator's choice whether or not to perform multiple loading attempts in order to fill the bucket. A total number of 30 excavation experiments were carried out, most of them requiring multiple attempts to achieve a full bucket. An average of 3.6 attempts per experiment was needed in order to obtain a bucket fill factor of 90%. By comparison, manual operation usually needs two or three attempts to achieve this bucket fill factor. This performance may seem inferior to previous published work: however, there are other factors involved that prevent direct comparison of the results. Equipment, type of ore, and mining method should be considered. Thus, comparison to the human operators of the specific mining site should be preferred. It is important to mention that the main driver for automating the loading process is to increase the safety of workers rather than obtain higher efficiency. In this regard, the proposed excavation algorithm fulfills our expectations. Since these experiments are time-consuming in an industry where time is an expensive resource, only enough experiments needed to validate the excavation algorithm were able to be executed. Part of our future work will be to carry out new experiments in an underground mine in order to validate the complete autonomous loading system, and to measure its performance more accurately. Despite this, the problem remains relevant and mining companies are looking forward to integrating autonomous loading to LHDs in their operations, as it would enable them to close the loop for a fully autonomous production cycle. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Modeling** & **Ground Truth** & **Predicted** & **Ground Truth** & **Predicted** \\
**Attempt** & **Width (m)** & **Width (m)** & **Inclination (\({}^{\circ}\))** & **Inclination (\({}^{\circ}\))** \\ \hline
1 & 3.25 & 2.89 & \(-\)53.0 & \(-\)52.6 \\ \hline
2 & 3.10 & 5.27 & \(-\)50.1 & \(-\)48.7 \\ \hline
3 & 3.10 & 3.16 & \(-\)52.4 & \(-\)50.5 \\ \hline
4 & 3.44 & 3.29 & \(-\)50.6 & \(-\)50.5 \\ \hline
5 & 3.20 & 3.72 & \(-\)50.0 & \(-\)53.4 \\ \hline
6 & 3.03 & 3.25 & \(-\)49.5 & \(-\)46.5 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Results of modeling extraction points. A video showing the operator's graphic interface while the system is autonomously performing an excavation procedure can be found in [[https://youtu.be/Oa11](https://youtu.be/Oa11) kTBjf2Y]([https://youtu.be/Oa11](https://youtu.be/Oa11) kTBjf2Y) (accessed on 7 September 2021). The system is now being installed and tested in a room and pillar mine in Germany, where it will be tested as a whole system. Conceptualization, C.T., M.M. and J.R.-d.-S.; methodology, M.M., C.T. and J.R.-d.-S.; software, C.T. ; validation, M.M. and C.T. ; resources, J.R.-d.-S.; data curation, C.T. ; writing--original draft preparation, C.T., M.M. and J.R.-d.-S.; writing--review and editing, C.T., M.M.