Fire ants link their legs and jaws together to form functional structures called self- assemblages. Examples include floating rafts, towers, bridges, and bivouacs. We investigate these self-assemblages of fire ants. Our studies are motivated in part by the vision of providing guidance for programmable robot swarms. The goal for such systems is to develop a simple programmable element from which complex patterns or behaviors emerge on the collective level. Intelligence is decentralized, as is the case with social insects such as fire ants.
In this combined experimental and theoretical study, we investigate the construction of two fire ant self-assemblages that are critical to the colony’s survival: the raft and the tower. Using time-lapse photography, we record the construction processes of rafts and towers in the laboratory. We identify and characterize individual ant behaviors that we consistently observe during assembly, and incorporate these behaviors into mathematical models of the assembly process. Our models accurately predict both the assemblages’ shapes and growth patterns, thus providing evidence that we have identified and analyzed the key mechanisms for these fire ant self-assemblages.
We also develop novel techniques using scanning electron microscopy and micro-computed tomography scans to visualize and quantify the internal structure and packing properties of live linked fire ants. We compare our findings to packings of dead ants and similarly shaped granular material packings to understand how active arranging affects ant spacing and orientation. We find that ants use their legs to increase neighbor spacing and hence reduce their packing density by one-third compared to packings of dead ants. Also, we find that live ants do not align themselves in parallel with nearest neighbors as much as dead ants passively do.
Our main contribution is the development of parsimonious mathematical models of how the behaviors of individuals result in the collective construction of fire ant assemblages. The models posit only simple observed behaviors based on local information, yet their mathe- matical analysis yields accurate predictions of assemblage shapes and construction rates for a wide range of ant colony sizes.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/50247 |
| Date | 13 January 2014 |
| Creators | Mlot, Nathaniel J. |
| Contributors | Hu, David L., Tovey, Craig A. |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | application/pdf |
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