Kinematics control of redundant manipulators using a CMAC neural network combined with a genetic algorithm

Yangmin Li; Sio Hong Leong

doi:10.1017/S0263574704000414

Kinematics control of redundant manipulators using a CMAC neural network combined with a genetic algorithm

Yangmin Li, Sio Hong Leong

Research output: Journal article publication › Journal article › Academic research › peer-review

19 Citations (Scopus)

Abstract

A method is proposed to solve the inverse kinematics and control problems of robot control systems using a cerebellar model articulation controller neural network combined with a genetic algorithm. Computer simulations and experiments with a 7-DOF redundant modular manipulator have demonstrated the effectiveness of the proposed method.

Original language	English
Pages (from-to)	611-621
Number of pages	11
Journal	Robotica
Volume	22
Issue number	6
DOIs	https://doi.org/10.1017/S0263574704000414
Publication status	Published - 1 Nov 2004
Externally published	Yes

Keywords

CMAC neural networks
Kinematics
Redundant manipulators

ASJC Scopus subject areas

Control and Systems Engineering

More information

10.1017/S0263574704000414

Cite this

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title = "Kinematics control of redundant manipulators using a CMAC neural network combined with a genetic algorithm",

abstract = "A method is proposed to solve the inverse kinematics and control problems of robot control systems using a cerebellar model articulation controller neural network combined with a genetic algorithm. Computer simulations and experiments with a 7-DOF redundant modular manipulator have demonstrated the effectiveness of the proposed method.",

keywords = "CMAC neural networks, Kinematics, Redundant manipulators",

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year = "2004",

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AU - Leong, Sio Hong

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N2 - A method is proposed to solve the inverse kinematics and control problems of robot control systems using a cerebellar model articulation controller neural network combined with a genetic algorithm. Computer simulations and experiments with a 7-DOF redundant modular manipulator have demonstrated the effectiveness of the proposed method.

AB - A method is proposed to solve the inverse kinematics and control problems of robot control systems using a cerebellar model articulation controller neural network combined with a genetic algorithm. Computer simulations and experiments with a 7-DOF redundant modular manipulator have demonstrated the effectiveness of the proposed method.

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KW - Kinematics

KW - Redundant manipulators

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DO - 10.1017/S0263574704000414

M3 - Journal article

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IS - 6

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Kinematics control of redundant manipulators using a CMAC neural network combined with a genetic algorithm

Abstract

Keywords

ASJC Scopus subject areas

More information

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