Proceedings ArticleDOI
Kernel machines for uncalibrated visual servoing of robots
Alexander Kale,Meetha Lal Meena,M. Gopal +2 more
- pp 364-369
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TLDR
The simulation results have shown that the robot visual servoing converges at the desired goal and KRLS is proved to be a better choice than SVR and LS-SVM Jacobian estimators.Abstract:
A new modelling method of image Jacobian estimation is presented for uncalibrated visual servoing of robots, in which a kernel recursive least squares (KRLS) technique is used for non-linear mapping between target image features and robot joint angles, and an image Jacobian expression is derived from the KRLS algorithm with gaussian kernel. The simulations of robot visual servoing with eye-in-hand camera configuration are conducted using the KRLS Jacobian estimator and the same are compared with SVR and LS-SVM Jacobian estimators. The simulation results have shown that the robot visual servoing converges at the desired goal and KRLS is proved to be a better choice.read more
Citations
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Journal ArticleDOI
An Uncalibrated Visual Servo Method Based on Projective Homography
TL;DR: An uncalibrated visual servo method based on projective homography, denoted as Projective Homography based Uncalibrated Visual Servoing (PHUVS), is proposed in this paper, in which a novel task function is devised to realize visual Servo without a prior knowledge of the camera intrinsic parameters and hand-eye relationships.
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