Global–local population memetic algorithm for solving the forward kinematics of parallel manipulators

Rohitash Chandra, Luc Rolland

Research output: Contribution to journalArticle

Abstract

Memetic algorithms (MA) are evolutionary computation methods that employ local search to selected individuals of the population. This work presents global–local population MA for solving the forward kinematics of parallel manipulators. A real-coded generation algorithm with features of diversity is used in the global population and an evolutionary algorithm with parent-centric crossover operator which has local search features is used in the local population. The forward kinematics of the 3RPR and 6–6 leg manipulators are examined to test the performance of the proposed method. The results show that the proposed method improves the performance of the real-coded genetic algorithm and can obtain high-quality solutions similar to the previous methods for the 6–6 leg manipulator. The accuracy of the solutions and the optimisation time achieved by the methods in this work motivates for real-time implementation of the 3RPR parallel manipulator.

Original languageEnglish
Pages (from-to)22-39
JournalConnection Science
Volume27
Issue number1
DOIs
Publication statusPublished - 2014
Externally publishedYes

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Manipulators
Kinematics
Evolutionary algorithms
Mathematical operators
Genetic algorithms

Cite this

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Global–local population memetic algorithm for solving the forward kinematics of parallel manipulators. / Chandra, Rohitash; Rolland, Luc.

In: Connection Science, Vol. 27, No. 1, 2014, p. 22-39.

Research output: Contribution to journalArticle

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AU - Rolland, Luc

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