Search from over 60,000 research works

Advanced Search

Architecture for Living Neuronal Network Control of a mobile robot

[thumbnail of DX_SSEC_Paper.doc]
DX_SSEC_Paper.doc - Other (1MB)
Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Xydas, D. (2008) Architecture for Living Neuronal Network Control of a mobile robot. In: SSE Systems Engineering Conference 2008, 25-26 Sep 2008, The University of Reading. (Unpublished)

Abstract/Summary

The intelligent controlling mechanism of a typical mobile robot is usually a computer system. Research is however now ongoing in which biological neural networks are being cultured and trained to act as the brain of an interactive real world robot – thereby either completely replacing or operating in a cooperative fashion with a computer system. Studying such neural systems can give a distinct insight into biological neural structures and therefore such research has immediate medical implications. The principal aims of the present research are to assess the computational and learning capacity of dissociated cultured neuronal networks with a view to advancing network level processing of artificial neural networks. This will be approached by the creation of an artificial hybrid system (animat) involving closed loop control of a mobile robot by a dissociated culture of rat neurons. This paper details the components of the overall animat closed loop system architecture and reports on the evaluation of the results from preliminary real-life and simulated robot experiments.

Item Type Conference or Workshop Item (Paper)
URI https://reading-clone.eprints-hosting.org/id/eprint/1109
Item Type Conference or Workshop Item
Refereed No
Divisions Science
Uncontrolled Keywords culture stimulation, dissociated neurones, machine learning, neural plasticity, robotic animats
Download/View statistics View download statistics for this item

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Search Google Scholar