Author Contributions
Conceptualization, J.W.; methodology, J.W.; software, J.W.; validation, J.W.; formal analysis, J.W.; investigation, J.W.; data curation, J.W.; Writing—Original draft preparation, J.W.; Writing—Review and editing, J.T. and A.T.; visualization, J.W.; supervision, J.T. and A.T.
Figure 1.
Behavioural hierarchy for those behaviours investigated within this paper.
Figure 1.
Behavioural hierarchy for those behaviours investigated within this paper.
Figure 2.
Graph displaying the results of the power consumption of a Psi Swarm robot increasing motor speed gradually. 10 repetitions were taken for these results and a trend line has been fit to the mean of these results and is shown in red.
Figure 2.
Graph displaying the results of the power consumption of a Psi Swarm robot increasing motor speed gradually. 10 repetitions were taken for these results and a trend line has been fit to the mean of these results and is shown in red.
Figure 3.
Graph showing average food gathered per energy unit consumed in a swarm of 20 foraging robots across 50 trials.
Figure 3.
Graph showing average food gathered per energy unit consumed in a swarm of 20 foraging robots across 50 trials.
Figure 4.
Screenshot of first simulated environment used. Food items are shown as black circles in the white environment, puck robots can be seen waiting in the nest area (light grey).
Figure 4.
Screenshot of first simulated environment used. Food items are shown as black circles in the white environment, puck robots can be seen waiting in the nest area (light grey).
Figure 5.
Screenshot of second simulated environment used. Food items are shown as black circles in the white environment, puck robots can be seen waiting in the nest area (light grey). Obstacles creating corridors are illustrated in dark grey.
Figure 5.
Screenshot of second simulated environment used. Food items are shown as black circles in the white environment, puck robots can be seen waiting in the nest area (light grey). Obstacles creating corridors are illustrated in dark grey.
Figure 6.
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 6.
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 7.
Three systems tested in in environment 2. 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 7.
Three systems tested in in environment 2. 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 8.
Hormone inspired sleep system tested in environment 1. 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 8.
Hormone inspired sleep system tested in environment 1. 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 9.
Hormone inspired sleep system tested in environment 2. 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 9.
Hormone inspired sleep system tested in environment 2. 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 10.
Combined hormone sleep and speed system tested in both environments. 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 10.
Combined hormone sleep and speed system tested in both environments. 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 11.
Environment used for all tests requiring terrain preference and categorisation of heterogeneous robots within the swarm.
Figure 11.
Environment used for all tests requiring terrain preference and categorisation of heterogeneous robots within the swarm.
Figure 12.
Effect of item target values driving different demands in the speed hormone on the percentage of robots taking preference to their optimal environment. The categorisation system running with no speed hormone present is marked as ‘no adapt’.
Figure 12.
Effect of item target values driving different demands in the speed hormone on the percentage of robots taking preference to their optimal environment. The categorisation system running with no speed hormone present is marked as ‘no adapt’.
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 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%).
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%).
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%).
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%).
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%).
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%).
Figure 17.
Results for energy efficiency as the number of robots in the swarm increases from 12 to 60.
Figure 17.
Results for energy efficiency as the number of robots in the swarm increases from 12 to 60.
Table 1.
Parameter values for the Return and Speed Hormones.
Table 1.
Parameter values for the Return and Speed Hormones.
| | | | |
---|
0.9977 | 5 | 0.999 | 9 | 0.01 |
Table 2.
Environment 1: Wilcoxon rank sum tests comparing the three systems for the tested item collection targets between 10–150 in terms of energy efficiency. Significant differences (indicated by a p value of <0.05) are highlighted in bold.
Table 2.
Environment 1: Wilcoxon rank sum tests comparing the three systems for the tested item collection targets between 10–150 in terms of energy efficiency. Significant differences (indicated by a p value of <0.05) are highlighted in bold.
System Type | Engineered vs. Static | Hormone vs. Static | Hormone vs. Engineered |
---|
Item Target Number | | | |
---|
10 | 0.8550 | 0.0330 | 0.0053 |
20 | 0.1648 | p < 0.0001 | p < 0.0001 |
30 | 0.1800 | p < 0.0001 | p < 0.0001 |
40 | 0.2626 | p < 0.0001 | p < 0.0001 |
50 | 0.0906 | p < 0.0001 | p < 0.0001 |
60 | 0.8227 | p < 0.0001 | p < 0.0001 |
70 | 0.0068 | p < 0.0001 | p < 0.0001 |
80 | 0.0262 | p < 0.0001 | p < 0.0001 |
90 | p < 0.0001 | p < 0.0001 | p < 0.0001 |
100 | p < 0.0001 | p < 0.0001 | p < 0.0001 |
110 | p < 0.0001 | p < 0.0001 | p < 0.0001 |
120 | p < 0.0001 | 0.0199 | p < 0.0001 |
130 | p < 0.0001 | 0.3984 | p < 0.0001 |
140 | p < 0.0001 | p < 0.0001 | p < 0.0001 |
150 | p < 0.0001 | p < 0.0001 | p < 0.0001 |
Table 3.
Environment 2: Wilcoxon rank sum tests comparing the three systems for the tested item collection targets between 10–150 in terms of energy efficiency. Significant differences (indicated by a p value of <0.05) are highlighted in bold.
Table 3.
Environment 2: Wilcoxon rank sum tests comparing the three systems for the tested item collection targets between 10–150 in terms of energy efficiency. Significant differences (indicated by a p value of <0.05) are highlighted in bold.
System Type | Engineered vs. Static | Hormone vs. Static | Hormone vs. Engineered |
---|
Item Target Number | | | |
---|
10 | 0.2482 | p < 0.0001 | p < 0.0001 |
20 | 0.6918 | p < 0.0001 | p < 0.0001 |
30 | 0.3432 | p < 0.0001 | p < 0.0001 |
40 | 0.1010 | p < 0.0001 | p < 0.0001 |
50 | 0.0817 | p < 0.0001 | p < 0.0001 |
60 | 0.0020 | p < 0.0001 | p < 0.0001 |
70 | 0.0002 | p < 0.0001 | p < 0.0001 |
80 | p < 0.0001 | p < 0.0001 | p < 0.0001 |
90 | p < 0.0001 | p < 0.0001 | p < 0.0001 |
100 | p < 0.0001 | p < 0.0001 | p < 0.0001 |
110 | p < 0.0001 | p < 0.0001 | p < 0.0001 |
120 | p < 0.0001 | p < 0.0001 | p < 0.0001 |
130 | p < 0.0001 | p < 0.0001 | p < 0.0001 |
140 | p < 0.0001 | p < 0.0001 | p < 0.0001 |
150 | p < 0.0001 | p < 0.0001 | p < 0.0001 |
Table 4.
Parameter values for the Return and Speed Hormones.
Table 4.
Parameter values for the Return and Speed Hormones.
| | | | | | |
---|
0.01 | 0.999 | 0.01 | 0.06 | 0.0.015 | 0.999 | 10 |
Table 5.
Wilcoxon rank sum tests comparing the combined hormone system with both the speed hormone system and the sleep hormone system, in both of the previously established environments. Tests were conducted for item collection targets between 10–150 in terms of energy efficiency. Significant differences (indicated by a p value of <0.05) are highlighted in bold.
Table 5.
Wilcoxon rank sum tests comparing the combined hormone system with both the speed hormone system and the sleep hormone system, in both of the previously established environments. Tests were conducted for item collection targets between 10–150 in terms of energy efficiency. Significant differences (indicated by a p value of <0.05) are highlighted in bold.
Item Target Number | Hormone Speed vs. Hormone Combination | Hormone Sleep vs. Hormone Combination |
---|
| (Environment 1) | (Environment 2) | (Environment 1) | (Environment 2) |
---|
10 | 0.9680 | 0.0047 | 0.2315 | 0.019 |
20 | 0.8830 | 0.0040 | 0.1653 | 0.0056 |
30 | 0.5290 | p < 0.0001 | 0.5831 | p < 0.0001 |
40 | 0.6017 | p < 0.0001 | 0.0810 | p < 0.0001 |
50 | 0.5290 | p < 0.0001 | p < 0.0001 | p < 0.0001 |
60 | 0.0809 | p < 0.0001 | p < 0.0001 | p < 0.0001 |
70 | 0.0283 | p < 0.0001 | p < 0.0001 | p < 0.0001 |
80 | 0.0047 | p < 0.0001 | p < 0.0001 | p < 0.0001 |
90 | 0.0675 | p < 0.0001 | p < 0.0001 | p < 0.0001 |
100 | 0.0024 | p < 0.0001 | p < 0.0001 | 0.0430 |
110 | 0.0910 | p < 0.0001 | 0.0024 | 0.0002 |
120 | 0.0763 | p < 0.0001 | 0.9042 | p < 0.0001 |
130 | 0.1081 | p < 0.0001 | 0.0211 | p < 0.0001 |
140 | 0.0227 | p < 0.0001 | p < 0.0001 | p < 0.0001 |
150 | 0.2648 | p < 0.0001 | p < 0.0001 | p < 0.0001 |
Table 6.
Speed Coefficients for Heterogeneous Robot Wheels on Different Terrains.
Table 6.
Speed Coefficients for Heterogeneous Robot Wheels on Different Terrains.
Terrain Type | Wood Suited Wheels | Grass Suited Wheels |
---|
Grass | 0.6 | 0.7 |
Wood | 1 | 0.8 |