Visual task identification and characterization using polynomial models

T. Kyriacou, Otar Akanyeti, Ulrich Nehmzow, R. Iglesias, S. A. Billings

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

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Abstract

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. In the spirit of the FIFA World Cup 2006 we demonstrate the viability of this approach by teaching a mobile robot to track a moving football, using the Narmax system identification technique.
Original languageEnglish
Title of host publicationProceedings of Towards Autonomous Robotic Systems 2006
Subtitle of host publicationIncorporating the Autumn Biro-Net Symposium
EditorsMark Witkowski, Ulrich Nehmzow, Chris Melhuish, Eddie Moxey, Alex Ellery
PublisherImperial College Press
Pages96-102
ISBN (Print)978-0-9553879-0-6, 978-0-9553879-0-6
Publication statusPublished - 30 Sept 2006
Externally publishedYes

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