Model-less visual servoing using modified simplex optimization

Kanako Miura; Koichi Hashimoto; Hikaru Inooka; Jacques A. Gangloff; Michel F. de Mathelin

doi:10.1007/s10015-005-0374-4

Model-less visual servoing using modified simplex optimization

Kanako Miura, Koichi Hashimoto, Hikaru Inooka, Jacques A. Gangloff, Michel F. de Mathelin

INF - System Information Sciences

Research output: Contribution to journal › Article › peer-review

6 Citations (Scopus)

Abstract

This article describes a robot positioning task with respect to a static target by visual servoing. The vision system is uncalibrated, and the kinematic model of the robot may be totally unknown. The displacements of the robot at joint level are generated in real time in order to minimize the objective function. The objective function includes the quadratic error between the current and the desired target images. A simplex method is used to minimize the objective function, and a Newton-like method is also used near convergence. We successfully validated this method with simulations under the graphic library OpenGL.

Original language	English
Pages (from-to)	131-135
Number of pages	5
Journal	Artificial Life and Robotics
Volume	10
Issue number	2
DOIs	https://doi.org/10.1007/s10015-005-0374-4
Publication status	Published - 2006 Nov

Keywords

Model-lessvisual servoing
Optimization
Uncalibrated visual servoing

ASJC Scopus subject areas

Biochemistry, Genetics and Molecular Biology(all)
Artificial Intelligence

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AU - Hashimoto, Koichi

AU - Inooka, Hikaru

AU - Gangloff, Jacques A.

AU - de Mathelin, Michel F.

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N2 - This article describes a robot positioning task with respect to a static target by visual servoing. The vision system is uncalibrated, and the kinematic model of the robot may be totally unknown. The displacements of the robot at joint level are generated in real time in order to minimize the objective function. The objective function includes the quadratic error between the current and the desired target images. A simplex method is used to minimize the objective function, and a Newton-like method is also used near convergence. We successfully validated this method with simulations under the graphic library OpenGL.

AB - This article describes a robot positioning task with respect to a static target by visual servoing. The vision system is uncalibrated, and the kinematic model of the robot may be totally unknown. The displacements of the robot at joint level are generated in real time in order to minimize the objective function. The objective function includes the quadratic error between the current and the desired target images. A simplex method is used to minimize the objective function, and a Newton-like method is also used near convergence. We successfully validated this method with simulations under the graphic library OpenGL.

KW - Model-lessvisual servoing

KW - Optimization

KW - Uncalibrated visual servoing

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Model-less visual servoing using modified simplex optimization

Abstract

Keywords

ASJC Scopus subject areas

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