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Visual task identification and characterisation using polynomial models

Akanyeti, O., Kyriacou, T., Nehmzow, U., Iglesias, R. and Billings, S.A. (2007) Visual task identification and characterisation using polynomial models. Robotics and Autonomous Systems, 55 (9). pp. 711-719. ISSN 0921-8890

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Developing robust and reliable control code for autonomous mobile robots is difficult, because the interaction between a physical robot and the environment is highly complex, subject to noise and variation, and therefore partly unpredictable. This means that to date it is not possible to predict robot behaviour based on theoretical models. Instead, current methods to develop robot control code still require a substantial trial-and-error component to the software design process. This paper proposes a method of dealing with these issues by a) establishing task-achieving sensor-motor couplings through robot training, and b) representing these couplings through transparent mathematical functions that can be used to form hypotheses and theoretical analyses of robot behaviour. We demonstrate the viability of this approach by teaching a mobile robot to track a moving football and subsequently modelling this task using the NARMAX system identification technique.

Item Type: Article
Copyright, Publisher and Additional Information: © 2007 Elsevier. This is an author produced version of a paper subsequently published in Robotics and Autonomous Systems. Uploaded in accordance with the publisher's self-archiving policy.
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield)
Depositing User: Miss Anthea Tucker
Date Deposited: 18 Oct 2012 10:29
Last Modified: 08 Feb 2013 17:40
Published Version: http://dx.doi.org/10.1016/j.robot.2007.05.016
Status: Published
Publisher: Elsevier
Refereed: No
URI: http://eprints.whiterose.ac.uk/id/eprint/74678

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