In this thesis, we develop a new language for genetic programming, specifically designed for high-level controller scripting on mobile robots. We then test this language against previous conventions on the Robots Everywhere Antbot platform. We develop a genetic programming framework using Python and the new language, to create corridor-following programs in a simple simulation. Using this framework, we conduct a variety of experiments to find good parameters and techniques that apply to this new language, which can evolve the best controllers. Our results suggest that hierarchical GP using a measure of elitism is likely the best solution, and that the new language is very capable of evolving solutions with a high degree of robustness and generality.
| Identifer | oai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/28474 |
| Date | January 2009 |
| Creators | August, Riley |
| Publisher | University of Ottawa (Canada) |
| Source Sets | Université d’Ottawa |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 128 p. |
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