A neural visual servoing in uncalibrated environments for robotic manipulators

In this paper we describe an image based approach for the visual control of robotic manipulators, which uses neural networks to cope with calibration inaccuracies and relevant changes in the geometry of the system. A fast sliding-mode based algorithm has been employed for the on-line training of thr...

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Bibliographic Details
Published in2004 IEEE International Conference on Systems, Man and Cybernetics Vol. 6; pp. 5362 - 5367 vol.6
Main Authors Cupertino, F., Giordano, V., Mininno, E., Naso, D., Turchiano, B.
Format Conference Proceeding
LanguageEnglish
Published Piscataway NJ IEEE 2004
Subjects
Applied sciences
Calibration
Computational geometry
Computer science; control theory; systems
Control systems
Control theory. Systems
Exact sciences and technology
Manipulators
Neural networks
Robot control
Robot kinematics
Robot vision systems
Robotics
Sliding mode control
Visual servoing
Sliding mode
Stereoscopy
Variable structure system
System with five degrees of freedom
Visual servoing
Calibration
Neural network
Fast algorithm
Moving body
Robotics
Visual control
Manipulator
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ISBN0780385667
9780780385665
ISSN1062-922X
DOI10.1109/ICSMC.2004.1401046

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Summary:In this paper we describe an image based approach for the visual control of robotic manipulators, which uses neural networks to cope with calibration inaccuracies and relevant changes in the geometry of the system. A fast sliding-mode based algorithm has been employed for the on-line training of three neural networks approximating the relationship between camera coordinates and world coordinates. The proposed approach is tested on the simulations on a 5-dof robotic manipulator that must track a moving object using a stand-alone stereoscopic vision system.
ISBN:0780385667
9780780385665
ISSN:1062-922X
DOI:10.1109/ICSMC.2004.1401046