Insect brain modeling for cognitive robotics
type: CreativeWork
description: During his history, man has always tried to imitate nature, to better know and understand himself. Thanks to the improvement of electronic technologies, the instruments with which he has followed this target have been improved, with results more and more realistic. Trying to artificially reproduce what nature has slowly realized and time tested, humans find amazing problems and solutions, that give a contribution to their life quality. Robots are the way humans try to reproduce animals, and study their interaction with the environment. Robots help to better know animals and animals help to create efficient robots. Analyzing animal brains leads to new control systems that could allow robots to be able to orient themselves, to take decisions, to survive alone, to complete dangerous missions, to be completely autonomous. Robot implementation could also lead to predictions, for basic science, deriving from emergent properties of models. The goal of this work is to design and simulate a simplified model of the brain of the Drosophila melanogaster. Fly has a small brain that shows a wealth of complex behaviors. Genetic techniques allow to remove parts of the Drosophila brain and the analysis of mutants behavior can lead to hypotheses about the functions of every single brain part. The bio-inspired models have been implemented in robotic structures and in robot simulators, in order to make comparisons between the real fly and the modeled one. This PhD research has been oriented toward two main lines: the first one has been directed to the insect brain modeling; the second line has been oriented to the simulation and the implementation of the model in robotic structures and then to the analysis of the behavior of the robots in order to obtain comparative results with real flies as well as predictions about the behavior of the real flies under particular circumstances. This thesis is divided in seven chapters. The first four chapters describe an original robotic architecture…
abstract: During his history, man has always tried to imitate nature, to better know and understand himself. Thanks to the improvement of electronic technologies, the instruments with which he has followed this target have been improved, with results more and more realistic. Trying to artificially reproduce what nature has slowly realized and time tested, humans find amazing problems and solutions, that give a contribution to their life quality. Robots are the way humans try to reproduce animals, and study their interaction with the environment. Robots help to better know animals and animals help to create efficient robots. Analyzing animal brains leads to new control systems that could allow robots to be able to orient themselves, to take decisions, to survive alone, to complete dangerous missions, to be completely autonomous. Robot implementation could also lead to predictions, for basic science, deriving from emergent properties of models. The goal of this work is to design and simulate a simplified model of the brain of the Drosophila melanogaster. Fly has a small brain that shows a wealth of complex behaviors. Genetic techniques allow to remove parts of the Drosophila brain and the analysis of mutants behavior can lead to hypotheses about the functions of every single brain part. The bio-inspired models have been implemented in robotic structures and in robot simulators, in order to make comparisons between the real fly and the modeled one. This PhD research has been oriented toward two main lines: the first one has been directed to the insect brain modeling; the second line has been oriented to the simulation and the implementation of the model in robotic structures and then to the analysis of the behavior of the robots in order to obtain comparative results with real flies as well as predictions about the behavior of the real flies under particular circumstances. This thesis is divided in seven chapters. The first four chapters describe an original robotic architecture…
author: TERMINI, PIETRO SAVIO
language: eng
keywords: robotics, neural network, insect brain
date published: 2012-12-10
date modified: 2026-07-24T01:35:08Z
provider: Università degli Studi di Catania
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Università degli studi di Catania

PropertyValue
property ID: Handle
value: https://hdl.handle.net/20.500.11769/587717