# Evaluating Swarm Robotics for Mining Environments: Insights into Model Performance and Application
## 7 Conclusions  
This study tests and evaluates the performance of three swarm robot models, namely ant, firefly, and honeybee, specifically in the context of mining operations, including ore detection, transportation, and selective extraction. The results indicate that the honeybee model may be particularly well-suited for operations requiring high precision and \begin{table}
\begin{tabular}{c c c c} \hline \hline \multicolumn{2}{c}{**Mining Methods**} & **Ant Model** & **Firefly Model** & **Honeybee Model** \\ \hline \multirow{4}{*}{Surface Mining Methods} & Open-Pit Mining & & \\ \cline{2-4}  & Strip Mining & & \\ \cline{2-4}  & Placer Mining & & \\ \cline{2-4}  & Dredging & & \\ \hline \multirow{4}{*}{Underground Mining Methods} & Room-and-Pillar Mining & & \\ \cline{2-4}  & Longwall Mining & & \\ \cline{2-4}  & Block Caving Mining & & \\ \cline{2-4}  & Cut-and-Fill Mining & & \\ \cline{2-4}  & Shrinkage Stoping & & \\ \cline{2-4}  & Sublevel Stoping & & \\ \hline \multirow{4}{*}{Specialized Mining Techniques} & In Situ Leaching & & \\ \cline{2-4}  & Solution Mining & & \\ \cline{2-4}  & Heap Leaching & & \\ \cline{2-4}  & Hydraulic Mining & & \\ \cline{2-4}  & Space Mining & & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Applications of swarm models in terrestrial mining. selectivity, such as extracting high-grade ones. The ant model, with its high reliability and task specialization, may be the most effective one for ore transportation, ensuring continuous and efficient material handling. The firefly model excels in ore detection, thanks to its robust communication and adaptability, and may be ideal for complex and dynamic environments where real-time feedback is essential. The honeybee model, distinguished by its hybrid control system, may be the optimal choice for selective ore extraction, allowing for precise targeting of high-grade ores and maximizing operational efficiency. However, the honeybee model has a reliability limitation, making it vulnerable under unknown and harsh conditions. Its reliance on centralized control caused significant performance drops in high-error conditions, and future improvements should focus on enhancing its decentralized components to mitigate single-point failures. The ant model, inspired by the leafcutter ants' task-allocation strategy and decentralized control systems, may be suitable for mining operations where there is no need for selectivity or strict control of the ore grade. It may be particularly well-suited for space mining, where human intervention and maintenance are impossible, and might excel in regolith extraction due to its decentralized control and task-allocation features. The firefly model, motivated by the bioluminescence of fireflies and employing behavior-based decentralized control, surpasses the ant model in terms of efficiency, scalability, and selectivity while also maximizing reliability. In underground mines, the firefly model may be useful for deposit location searches and may be applicable in hazardous or unknown environments, such as toxic gas mining and space mining, where decentralized control of swarm robots may allow for better location tracking, which is crucial when signal transmission may be delayed or non-existent. This study demonstrates that for the successful application of swarm robots in mining, it is crucial to choose the swarm model that best suits the specific characteristics and requirements of the mining environment under consideration. For example, ant and firefly models involve decentralized control with command signals being sent and may be suitable for space mining where signal transmission is limited, while the honeybee model involves high precision and may be applied in selective mining, room-and-pillar mining, cut-and-fill mining, and in situ leaching, which requires high-precision extraction.