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

Yangmin Li, Xiaoping Liu, Zhaoyang Peng, Yugang Liu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

13 Citations (Scopus)

Abstract

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.
Original languageEnglish
Pages (from-to)509-517
Number of pages9
JournalRobotica
Volume20
Issue number5
DOIs
Publication statusPublished - 1 Sep 2002
Externally publishedYes

Keywords

  • Modal analysis
  • Modular robots
  • Parameter identification
  • Vibration control

ASJC Scopus subject areas

  • Control and Systems Engineering

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