## 3 HIBAS Implementation for Control of a Foraging System with Deviating Motor Speeds
### Results
#### 3.5.1 Environment 1--Square Open Arena  
Visual inspection of the first environment (Figure 6) shows that the static speed system has a fairly consistent level of food collected per energy unit used as the demand increases. This is expected due to the lack of change in speed, though the lowest target number for item collection does see a drop in energy efficiency when compared with the rest of the collection rates. This is because not all of the robots in the swarm will have returned to the nest by the time the experiment terminates having reached the target number of items. This will result in unnecessary energy consumption from the robots unable to return food items within the short period of the experiment. The downside of this consistent energy consumption is the inability to reach greater item target numbers. This drawback can be seen in the discolouration of the box plots starting at 100 food items required and saturating to red, indicating a collection of less than 70% of the required items, by 130 required items. Disregarding the lack of success in large item demand experiments, the results from the static speed system provide a strong baseline for energy efficiency. Giving a clear target for the other two more intelligent systems to aim for. When inspecting the results of the two adaptive system it is immediately obvious that target collections are met more consistently with the demand function introduced to the system, with discolouration starting at 120 in the engineered system and 130 in the hormone system. In the engineered system the collection rate drops to approximately 80% by the 150 item goal while the hormone system still manages to collect upwards of 90%. In terms of energy efficiency the engineered adaptive system follows a similar initial trend to the none adaptive system. The similarity is maintained until an item target of 50, at which point the engineered system becomes increasingly less efficient. Table 2 supports this, showing that there is no significant difference in the data sets of the Engineered and static systems until 70 target items. At this point the systems diverge as the engineered system consumes more energy. These results also show that the hormone system managed to outperform both systems in regard to energy efficiency. With a significant difference versus the engineered adaptation and increased median result at every collection target excluding 10, the hormone system results can be seen arcing over those of the engineered system after starting at a similar point. Similarly, when compared to the static system, the hormone system shows significant increases to the food collected per energy used in  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**System Type** & **Engineered vs. Static** & ** Hormone vs. Static** & ** Hormone vs. Engineered** \\ \hline
**Item Target Number** & & & \\ \hline
10 & 0.8550 & 0.0330 & 0.0053 \\
20 & 0.1648 & \(p\) \textless{} 0.0001 & \(p\) \textless{} 0.0001 \\
30 & 0.1800 & \(p\) \textless{} 0.0001 & \(p\) \textless{} 0.0001 \\
40 & 0.2626 & \(p\) \textless{} 0.0001 & \(p\) \textless{} 0.0001 \\all cases but targets of 10, 120 and 130 items. The similarity in energy efficiency of the hormone and speed systems at item targets of 120 and 130 can be explained by the speed increase of the hormone system in cases of very high item demand, actually reaching collection targets while the static system misses them by a large margin. The efficiency of the hormone system over the static and engineered systems was explained by three factors:  
**Sensitivity:**: The hormone system is sensitive to collisions and capable of not only returning robots to the nest due to collisions, but also reducing speed due to the prolonged influence of collisions. **Dispersion:**: Rather than consistent speeds, or speeds of specific increments, the speeds of the hormone driven robots fluctuate during the search. Thus, dispersion is a by-product of efficiency as speed will be diverse amongst the swarm.