Image-based Visual System Research Articles

Adaptive Visual Servoing of Robot Manipulators without Measuring the Image Velocity

The direct adaptive control of planar robot manipulators through visual servoing is considered. A solution is developed for image-based visual systems to allow tracking of a desired trajectory, when both camera calibration and robot dynamics are uncertain. In order to solve the MIMO parameter adaptive problem without using image velocity information, the adaptive camera calibration is formulated as a relative degree two MIMO adaptive control problem. A recently proposed Lyapunov/passivity-based adaptive control for relative degree two MIMO system based on SDU factorization is applied. The resulting adaptive calibration is then combined with an adaptive motion controller for the manipulator, which takes into account its uncertain nonlinear dynamics. The overall stability of the adaptive visual servoing system can be proved thanks to the explicit Lyapunov-like functions of both adaptation schemes.

Robust Decoupling Control of an Image-Based Visual System

In this paper, nonlinear control theory is applied to solve the problem of controlling the position of a robot camera with respect to an object. An image-based state space representation of a robot camera-object interaction model is derived, assuming affine shape transformations in the image space and local linear approximation of visible object's surface. The image-based visual system is stabilized by a robust decoupling control law, which ensure asymptotic stability except at image singularities, assuming exact model and state measurements. In the presence of multiplicative uncertainties in the decoupling matrix and additive uncertainties in the object motion and in the state measurements, the closed-loop system behavior is characterised by an attractor. Simulation results validate the theoretical framework both in terms of system convergence and control robustness.