Task Characterisation and Cross-Platform Programming Through System Identification

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, it is subject to noise and variation, and therefore partly unpredictable. This means that to date it is not possible to predi...

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Main Authors: Roberto Iglesias, Urlich Nehmzow, Theocharis Kyriacou, Steve Billings
Format: Article
Language:English
Published: SAGE Publishing 2008-11-01
Series:International Journal of Advanced Robotic Systems
Online Access:http://www.intechopen.com/articles/show/title/task_characterisation_and_cross-platform_programming_through_system_identification
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spelling doaj-e259356336c84f4191e51689ec0420172020-11-25T03:32:21ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88061729-88142008-11-0124Task Characterisation and Cross-Platform Programming Through System IdentificationRoberto IglesiasUrlich NehmzowTheocharis KyriacouSteve BillingsDeveloping robust and reliable control code for autonomous mobile robots is difficult, because the interaction between a physical robot and the environment is highly complex, it is 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. Such iterative refinement could be reduced, we argue, if a more profound theoretical understanding of robot-environment interaction existed. In this paper, we therefore present a modelling method that generates a faithful model of a robot's interaction with its environment, based on data logged while observing a physical robot's behaviour. Because this modelling method - nonlinear modelling using polynomials - is commonly used in the engineering discipline of system identification, we refer to it here as "robot identification". We show in this paper that using robot identification to obtain a computer model of robot environment interaction offers several distinct advantages:<br/> 1. Very compact representations (one-line programs) of the robot control program are generated<br/> 2.The model can be analysed, for example through sensitivity analysis, leading to a better understanding of the essential parameters underlying the robot's behaviour, and <br/> 3. The generated, compact robot code can be used for cross-platform robot programming, allowing fast transfer of robot code from one type of robot to another.<br/> We demonstrate these points through experiments with a Magellan Pro and a Nomad 200 mobile robot. http://www.intechopen.com/articles/show/title/task_characterisation_and_cross-platform_programming_through_system_identification
collection DOAJ
language English
format Article
sources DOAJ
author Roberto Iglesias
Urlich Nehmzow
Theocharis Kyriacou
Steve Billings
spellingShingle Roberto Iglesias
Urlich Nehmzow
Theocharis Kyriacou
Steve Billings
Task Characterisation and Cross-Platform Programming Through System Identification
International Journal of Advanced Robotic Systems
author_facet Roberto Iglesias
Urlich Nehmzow
Theocharis Kyriacou
Steve Billings
author_sort Roberto Iglesias
title Task Characterisation and Cross-Platform Programming Through System Identification
title_short Task Characterisation and Cross-Platform Programming Through System Identification
title_full Task Characterisation and Cross-Platform Programming Through System Identification
title_fullStr Task Characterisation and Cross-Platform Programming Through System Identification
title_full_unstemmed Task Characterisation and Cross-Platform Programming Through System Identification
title_sort task characterisation and cross-platform programming through system identification
publisher SAGE Publishing
series International Journal of Advanced Robotic Systems
issn 1729-8806
1729-8814
publishDate 2008-11-01
description 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, it is 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. Such iterative refinement could be reduced, we argue, if a more profound theoretical understanding of robot-environment interaction existed. In this paper, we therefore present a modelling method that generates a faithful model of a robot's interaction with its environment, based on data logged while observing a physical robot's behaviour. Because this modelling method - nonlinear modelling using polynomials - is commonly used in the engineering discipline of system identification, we refer to it here as "robot identification". We show in this paper that using robot identification to obtain a computer model of robot environment interaction offers several distinct advantages:<br/> 1. Very compact representations (one-line programs) of the robot control program are generated<br/> 2.The model can be analysed, for example through sensitivity analysis, leading to a better understanding of the essential parameters underlying the robot's behaviour, and <br/> 3. The generated, compact robot code can be used for cross-platform robot programming, allowing fast transfer of robot code from one type of robot to another.<br/> We demonstrate these points through experiments with a Magellan Pro and a Nomad 200 mobile robot.
url http://www.intechopen.com/articles/show/title/task_characterisation_and_cross-platform_programming_through_system_identification
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