Enhancing the Neuro-Controller Design Process for the Myon Humanoid Robot

Please use this identifier to cite or link to this item:
https://nbn-resolving.org/urn:nbn:de:gbv:700-2013071711000
Open Access logo originally created by the Public Library of Science (PLoS)
Full metadata record
DC FieldValueLanguage
dc.creatorRempis, Christian
dc.creatorHild, Manfred
dc.creatorPasemann, Frank
dc.date.accessioned2013-07-17T15:53:05Z
dc.date.available2013-07-17T15:53:05Z
dc.date.issued2013-07-17T15:53:05Z
dc.identifier.citationTechnical Report of the Institute of Cognitive Science, University of Osnabrück, 2013
dc.identifier.urihttps://repositorium.ub.uni-osnabrueck.de/handle/urn:nbn:de:gbv:700-2013071711000-
dc.description.abstractDeveloping neural networks for the behavior control of autonomous robots can be a time-consuming task. This is especially the case for the new generation of complex robots with many sensors and motors – such as humanoid robots –, for which the networks with hundreds of neurons can become comparably large. Looking at the corresponding controller design workflow, a number of properties can be identified that slow down the development process: (1) The difficulty to create, handle and comprehend the large neuro-controllers, (2) the intricate debugging of neuro-controllers on the hardware, (3) delays caused by frequent time-consuming uploads of controllers to the hardware, (4) potential damaging of the robot and (5) the overall maintenance effort. This article proposes several measures to improve this workflow with respect to the mentioned problems. Some proposed improvements are realized by using sophisticated evolutionary robotics development software and suitable graphical network design tools. Such software, here in particular the Neurodynamics and Evolutionary Robotics Development Toolkit (NERD), significantly improves the network design process, specifically by allowing the development partially in simulation, by allowing a visual design of controllers with graphical network editors and by using suited neuro-evolution algorithms. Other improvements are based on proper neuro-modules that can be used to increase the usability of existing controllers. Bundled together, the proposed measures lead to a faster development of neuro-controllers. The proposed methods are demonstrated exemplarily with the Myon humanoid robot, but they can be applied also to other robots with similar properties and thus can help to improve the workflow for the neuro-controller design on such robot hardware.eng
dc.rightsNamensnennung-Keine Bearbeitung 3.0 Unported-
dc.rights.urihttp://creativecommons.org/licenses/by-nd/3.0/-
dc.subjectRoboticseng
dc.subjectArtificial Neural Networkseng
dc.subjectNeuroevolutioneng
dc.subject.ddc000 - Informatik, Wissen, Systeme
dc.titleEnhancing the Neuro-Controller Design Process for the Myon Humanoid Roboteng
dc.typeVerschiedenartige Texte [report]
vCard.ORGFB8
Appears in Collections:FB08 - Hochschulschriften

Files in This Item:
File Description SizeFormat 
rempis2013.pdfPDF des Technischen Reports813,82 kBAdobe PDF
rempis2013.pdf
Thumbnail
View/Open
rempis-hild-pasemann-2013.zipLatex Sourcen des Technischen Reports1,69 MBZIP
rempis-hild-pasemann-2013.zip
View/Open


This item is licensed under a Creative Commons License Creative Commons