*5.3. System Combining Sleep, Speed and Preference Hormones*

To observe the performance of this new system, the various combinations of hormone systems were tested in combination in the new multi-terrain environment. First the preference system was tested on its own, the results from this are illustrated in Figure 13. These results would act as a baseline to the additional systems as results from this new environment, with new task complexities, would be incomparable with data from previous experiments.

When adding the sleep hormone to the system (results illustrated in Figure 14), results for energy efficiency are consistently raised past the first item targets of 5, as shown by median results increasing by approximately 25% for item targets past 70. While there is a large improvement in terms of energy efficiency, adding the sleep hormone only results in a slight increase to collection rate, with the cut off point for collection becoming poor (below 90% of the target item collection) shifted from 80 to 90.

**Figure 13.** Hormone preference system tested in the environment containing two difference terrain types. Target number for items collected ranged from 10 to 150 items of food. Percentage of the items requested versus those collected by the end of the simulation is indicated by colour (Green 100% and Red < 70%).

**Figure 14.** Hormone preference system, combined with the sleep hormone system tested in the environment containing two difference terrain types. Target number for items collected ranged from 10 to 150 items of food. Percentage of the items requested versus those collected by the end of the simulation is indicated by colour (Green 100% and Red < 70%).

When the speed hormone is added to the system in the absence of the sleep hormone energy efficiency suffers considerably. This is seen with the consistent drop in efficiency results illustrated in Figure 15 when compared to the baseline results. However, this drop in efficiency is traded for a substantial improvement to collection rate, moving the cut off point for poor collection to 120 target items. These results are expected with the additional speed fluctuation and if the results from previous hormone combinations hold consistent, the addition of the sleep system to the preference/speed hormone regulation should amend the poor energy efficiency while maintaining the item collection rate.

**Figure 15.** Hormone preference system, combined with the speed hormone system tested in the environment containing two difference terrain types. Target number for items collected ranged from 10 to 150 items of food. Percentage of the items requested versus those collected by the end of the simulation is indicated by colour (Green 100% and Red < 70%).

Combining all three systems (results illustrated in Figure 16) provides the best result in terms of item collection, maintaining adequate collection until the 130 target item trial. Simultaneously, the system that combines all three hormone types is capable of accomplishing competitive values for energy efficiency. These values show improvements across all item targets for the standard preference and combined speed hormone results. The three hormone system only marginally under performs in energy efficiency versus the combined preference and sleep system, although it shows much greater item collection percentages. These results suggest that the fully combined system as the strongest of the system permutations when considering both item collection and energy efficiency.

**Figure 16.** Hormone preference system combined with both the sleep and speed hormone system, tested in the environment containing two difference terrain types. Target number for items collected ranged from 10 to 150 items of food. Percentage of the items requested versus those collected by the end of the simulation is indicated by colour (Green 100% and Red < 70%).

### **6. Scalability of Final Amalgamated Hormone System**

To introduce a key element of difficulty to the system presented in this paper a scalability test was conducted. With more robots in the swarm, the more difficult it will be to move effectively within the environment without slowing due to clutter. Along side this, with greater swarm density robots may receive over-stimulation from the transmitted hormones of the increased number of robots or there may be too much competition for food items, with multiple robots travelling to the same item simultaneously. With these additional negative features present it will be difficult for robots to form accurate preferences to terrain due to the fact that these negative features may have a greater effect on performance than the speed variance provided by the different wheel types.

The scalability tests were conducted by increasing the number of robots in each simulation by 6 for each set of trials, testing swarm sizes ranging between 12 and 60. In each experiment the target number of items was set to 100 and in every test all of these items were retrieved. The experiments conducted terminated after 500 simulated seconds or if the target number of items was reached. The item target of 100 was chosen due to the variability in performance at said target number across each of the previously tested systems. This indicated that this number of items is an area of interest, providing substantial challenge to some systems while still an achievable goal to others.

The results of the scalability test can be seen illustrated in Figure 17. It can be seen that energy efficiency decreases linearly with the increase in members of the swarm. This was expected with the increased difficulty to the task as, while the amalgamated system is able to augment performance with a given swarm size, additional or unneeded robots will still create detriment to performance. Through the linear nature of this performance degradation, a user can select a swarm size which is suitable for a given task, trading off energy efficiency for the speed at which items should be gathered.

**Figure 17.** Results for energy efficiency as the number of robots in the swarm increases from 12 to 60.
