Abstract
In this paper, a visual servoing robotic control scheme of fast convergence and calibration-free is proposed. The objective of this paper is to achieve a better convergence around the equilibrium for uncalibrated visual servoing systems. Moreover, there are threefold unknown parameters, the visual kinematic parameters, the dynamic parameters and the parameters of the feature points, considered in the design of the proposed control scheme. In order to achieve the above control objective, the finite-time tracking controller and three adaptive laws are proposed. The adaptability to the unknown parameters is guaranteed by the online adaptive laws. The finite-time convergence is achieved by the continuously non-smooth fractional order function in the controller. The rigorously mathematic proof of stability is given by homogeneous theory and the Lyapunov function formalism. Three real-time experiments are conducted to demonstrate the practical performance of the proposed scheme.
Highlights
The past decades have witnessed the rapid development of visual servoing robotic control
We investigate the fast convergence of IBUVS which considers unknown visual kinematics, unknown robotic dynamics and a time-varying image depth of the reference features
In the field of IBUVS control, the method for the fast trajectory tracking by using finite-time control theory is originally proposed to address the problem of slow convergence at the equilibrium
Summary
The past decades have witnessed the rapid development of visual servoing robotic control. As a combination of computer vision and robot control, once appeared, the visual servoing control has attracted extensive attention of researchers, which is regarded as one of the most promising techniques. The uncalibrated visual servoing control is free of tedious calibration, which is laborsaving and flexible to the different parameters. The visual servoing control technique can be divided into three classes: image-based (IB), position-based (PB) and homography-based (HB). Compared with PB and HB, the image-based visual servoing control method purely employs information of the image errors, which is helpful to high degree of calibration-free [1], [2]. We will focus on the image-based uncalibrated visual servoing control method in this paper
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