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 |
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Pages (from-to) | 131-135 |
Number of pages | 5 |
Journal | Artificial Life and Robotics |
Volume | 10 |
Issue number | 2 |
DOIs | |
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