Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/808884
- Title
- Machine learning with AIBO robots in the four legged league of RoboCup
- Author/Creator
-
Chalup, Stephan K.;
Murch, Craig L.;
Quinlan, Michael J.
- Description
- Robot learning is a growing area of research at the intersection of robotics and machine learning. The main contributions of this paper include a review of how machine learning has been used on Sony AIBO robots and at RoboCup, with a focus on the four-legged league during the years 1998-2004. The review shows that the application-oriented use of machine learning in the four-legged league was still conservative and restricted to a few well-known and easy-to-use methods such as standard decision trees, evolutionary hill climbing, and support vector machines. Method-oriented spin-off studies emerged more frequently and increasingly addressed new and advanced machine learning techniques. Further, the paper presents some details about the growing impact of machine learning in the software system developed by the authors' robot soccer team - the NUbots.
- Relation
- IEEE Transactions on Systems, Man and Cybernetics, Part C: Applications and Reviews Vol. 37, Issue 7, p. 297-310
- Publisher Link
- http://dx.doi.org/10.1109/TSMCC.2006.886964
- Date
- 2007
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Keyword(s)
-
machine learning;
RoboCup;
Sony AIBO;
robot soccer;
robot vision systems;
legged locomotion;
learning systems
- Resource Type
- journal article
- Rights
- Copyright © 2007 IEEE. Reprinted from IEEE Transactions on Systems, Man and Cybernetics, Part C. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of University of Newcastle's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
- Identifier
- http://hdl.handle.net/1959.13/808884
- Identifier
- ISSN:1094-6977
- Language
- eng
- Reviewed
- Full Text
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