Aslan, Bilal and Nitschke, Geoff (2024) Morpho-Material Evolution for Automated Robot Design, Proceedings of Genetic and Evolutionary Computation Conference (GECCO 2024), 14-18 July, Melbourne, Australia, ACM.
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Abstract
Multi-Level Evolution (MLE) has been demonstrated for effective robot designs using a bottom-up approach, first evolving which materials to use for modular components and then how these components are connected into a functional robot design. This paper evaluates hierarchical MLE robotic design, as an evolutionary design method on various task (robot ambulation) environments in comparison to human designed robots (pre-designed robot controller-morphology couplings). Results indicate that the MLE method evolves robots that are effective across increasingly difficult (locomotion) task environments, out-performing pre-designed robots, and thus provide further support for the efficacy of MLE as an evolutionary robotic design method. Furthermore, results indicate the MLE method enables the evolution of suitable robotic designs for various environments, where such designs would be non-intuitive and unlikely in conventional robotic design.
| Item Type: | Conference paper |
|---|---|
| Subjects: | Computing methodologies > Artificial intelligence Computer systems organization > Embedded and cyber-physical systems > Robotics |
| Date Deposited: | 19 Jun 2024 11:13 |
| Last Modified: | 19 Jun 2024 11:13 |
| URI: | https://pubs.cs.uct.ac.za/id/eprint/1661 |
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