An iterative robot-image Jacobian approximation of image-based visual servoing for joint limit avoidance

I Siradjuddin, TM McGinnity, SA Coleman, Laxmidhar Behera

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

In this paper, we propose a new method addressing the robot-image Jacobianapproximation of image-based visual servoing (IBVS) for a redundant manipulator. Therobot-image Jacobian is approximated iteratively and is a model free. A linearised model of therobot-image Jacobian is applied, based on the first order Taylor series approximation. A weightedleast norm solution is induced in a pseudo inverse computation of the approximated robot-imageJacobian. The resulting control law then can be used for visual servoing tasks with joint limitavoidance capability using both a static target or moving target. The self-motion of the robotjoints resolves the redundancy during visual servoing tasks when one or more joints areapproaching their joint limits.A design and stability analysis of the proposed method is discussed in this paper.Simulated and real-time experiments using a 7 DOF PowerCube robot manipulator areconducted. The IBVS is configured using a monovision eye-in-hand system configuration. Thesystem behaviour and performances of the proposed method are presented and analysed.
LanguageEnglish
Pages227-239
JournalInternational Journal of Mechatronics and Automation
Volume2
Issue number4
DOIs
Publication statusPublished - 24 May 2012

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Visual Servoing
Visual servoing
Robot
Robots
Approximation
Redundant manipulators
Taylor series
Redundant Manipulator
Pseudo-inverse
Robot Manipulator
Moving Target
Manipulators
Redundancy
Stability Analysis
Resolve
First-order
Real-time
Norm
Configuration
Target

Cite this

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An iterative robot-image Jacobian approximation of image-based visual servoing for joint limit avoidance. / Siradjuddin, I; McGinnity, TM; Coleman, SA; Behera, Laxmidhar.

In: International Journal of Mechatronics and Automation, Vol. 2, No. 4, 24.05.2012, p. 227-239.

Research output: Contribution to journalArticle

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