# Evaluating Swarm Robotics for Mining Environments: Insights into Model Performance and Application
## 5 Results and Discussions
### Performance and Resources Metrics
#### 5.7.2 Energy Consumption  
In this study, the energy consumption of the considered four swarm robot models is evaluated to measure their efficiency in various mining scenarios. To ensure a fair and consistent comparison, uniform assumptions about the energy consumption rates of important tasks across all models has been assumed. Each model is assumed to use 1 joule per second (J/s) when moving, 2 J/s when communicating, 3 J/s when exploring, and 6 J/s when transporting. These numbers are average energy requirements chosen based on the characteristics of the tasks. Specifically, transporting requires more energy due to the need to move the collected ore, while communication consumes less energy for coordination and data exchange. Exploration involves moderate navigation and scanning energy consumption. Energy consumption for the four models is illustrated in Figure 17.  
The four swarm models have different energy consumption patterns, which helps to understand how their control strategies, task allocation, and interaction protocols affect the overall energy distribution. The baseline model accounted for 40.3% of the total energy consumption of all models, with the highest energy consumption of 15.3 KJ. Due to the lack of task allocation, communication, and coordination, each robot is forced to handle exploration and transportation tasks independently, which leads to high energy consumption. Redundant operations caused by an inefficient task management system resulted in higher energy demand. Since each robot uses energy to complete each task, the baseline model consumed more energy and was less efficient than the other models. Of the total energy, the ant model used total energy consumption of 11.14 KJ or 29.4% of the total energy consumption of all models. Since the robots are divided into two groups, this model benefited from the division of labor. The decentralized control mechanism of the ant model ensured that tasks are efficiently allocated, thereby reducing idle time and preventing any group of robots from using too much energy. This made the energy distribution more consistent and stable than for the baseline model, which assumes that tasks such as exploration and transportation are repeated, thus leading to energy inefficiency. The firefly model used total energy consumption of 8.12 KJ, or 21.4% of the total energy. The necessity of the initial exploration and the activation of the bioluminescent communication system caused its energy consumption to peak at 1 min 45 s. The robots use more energy in this phase, because they communicate with one another by emitting light signals. But when the beacon is activated, the exploration becomes more focused and targeted, minimizing unnecessary searches. Therefore, the energy demand is reduced. This efficient communication mechanism balanced energy consumption by reducing unnecessary actions, which works in the firefly model's favor once communication is established. The honeybee model was the most energy efficient, with an energy consumption of only 3.38 KJ or 8.9% of the total energy. This model showed a dynamic energy-consumption pattern, with energy consumption peaking in the first minute due to the intensive exploration and communication of the scout robots. Thereafter, around at 1 min 45 s, the recruitment process takes over and energy consumption drops sharply because most robots are waiting for the master robot's signal and task assignment. Once harvesting begins, energy consumption  
Figure 17: Energy consumption for the four models in a standard scenario. (**a**) Energy consumption distribution across time, (**b**) Total energy consumption comparison. The blue dotted line in (**b**) represents the energy consumption trend across the models, showing a decrease from the baseline model to the honeybee model. rises but remains much lower than for the other models. The honeybee model hybrid control system (combining centralized and decentralized elements) ensured efficient energy use by reducing idle time and meaningless operations.