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The identification of joint parameters for modular robots using fuzzy theory and a genetic algorithm

Published online by Cambridge University Press:  06 September 2002

Yangmin Li ,
Xiaoping Liu ,
Zhaoyang Peng  and
Yugang Liu
Yangmin Li
Affiliation:
Faculty of Science and Technology, University of Macau, Macao SAR (P.R. China).
Xiaoping Liu
Affiliation:
Automation School, Beijing University of Posts and Telecommunications, Beijing (P.R. China).
Zhaoyang Peng
Affiliation:
Automation School, Beijing University of Posts and Telecommunications, Beijing (P.R. China).
Yugang Liu
Affiliation:
Automation School, Beijing University of Posts and Telecommunications, Beijing (P.R. China).
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Summary

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This paper discusses a technique for identifying the joint parameters of a modular robot in order to study the dynamic characteristics of the whole structure and to realise dynamic control. A method for identifying the joint parameters of the structure applying fuzzy logic combined with a genetic algorithm has been studied using a 9-DOF modular redundant robot. A Genetic Algorithm was used in the fuzzy optimisation, which helped to avoid converging to locally optimal solutions and made the results identified much more reasonable. The joint parameters of a 9-DOF modular redundant robot have been identified.

Keywords

Parameter identificationModular robotsModal analysisVibration control

Information

Type
Research Article
Information
Robotica , Volume 20 , Issue 5 , September 2002 , pp. 509 - 517
Copyright
Copyright © Cambridge University Press 2002

References

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