Visual task identification and characterization using polynomial models

被引：6

作者：

Akanyeti, O. ^{[1
]}

Kyriacou, T.

Nehmow, U.

Iglesias, R.

Billings, S. A.

机构：

[1] Univ Essex, Dept Comp Sci, Colchester CO4 3SQ, Essex, England

[2] Univ Santiago de Compostela, Santiago De Compostela, Spain

[3] Univ Sheffield, Dept Automat Control & Syst Engn, Sheffield S10 2TN, S Yorkshire, England

来源：

ROBOTICS AND AUTONOMOUS SYSTEMS | 2007年 / 55卷 / 09期

基金：

英国工程与自然科学研究理事会;

关键词：

autonomous mobile robots; system identification; polynomials;

D O I：

10.1016/j.robot.2007.05.016

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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. (c) 2007 Elsevier B.V. All rights reserved.

引用

页码：711 / 719

页数：9

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