In this paper a visual servoing architecture based on a parallel robot for the tracking of faster moving objects with unknown trajectories is proposed. The control strategy is based on the prediction of the future position and velocity of the moving object. The synthesis of the predictive control law is based on the compensation of the delay introduced by the vision system. Demonstrating by experiments, the high-speed parallel robot system has good performance in the implementation of visual control strategies with high temporary requirements.

Machining by parallel planes is a widely used strategy for end-milling of free-form surfaces on 3-axis numerically controlled machines. In industry, this type of machining is generally performed with a hemispherical tool. However, numerous studies have shown the benefits of torus-end mills over ball-end or flat-end mills. More than anything, the machining direction has much influence on productivity while using a torus-end mill. In this context, the choice of the machining direction is of paramount importance when using a torus-end mill in the machining of free-form surfaces. This paper presents an optimization of part machining direction allowing the machining time to be minimized while respecting the maximum imposed scallop height. This optimization methodology is then applied to an industrial part and measurements are performed on this part. The study highlights the interest of optimizing the machining direction and the benefits that can be drawn with respect to machining using a non-optimized direction.

This paper describes a comparative study of performance between the estimated image Jacobian that come from taking into account the epipolar geometry in a system of two cameras, and the well known analytic image Jacobian that is utilized for most applications in visual servoing. Image Based Visual Servoing architecture is used for controlling a 3 DOF articular system using two cameras in eye to hand configuration. Tests in static and dynamic cases were carried out, and showed that the performance of estimated Jacobian by using the properties of the epipolar geometry is such as good and robust against noise as the analytic Jacobian. This fact is considered as an advantage because the estimated Jacobian does not need laborious previous work prior to control task in contrast to the analytic Jacobian does.

This paper describes a comparative study of performance between the estimated image Jacobian that come from taking into account the geometry epipolar of a system of two cameras, and the well known analytic image Jacobian that is utilized for most applications in visual servoing. Image Based Visual Servoing architecture is used for controlling a 3 d.o.f. articular system using two cameras in eye to hand configuration. Tests in static and dynamic cases were carried out, and showed that the performance of estimated Jacobian by using the properties of the epipolar geometry is such as good and robust against noise as the analytic Jacobian. This fact is considered as an advantage because the estimated Jacobian does not need laborious previous work prior the control task in contrast to the analytic Jacobian does.

New Visual Servoing Control Strategies in Tracking Tasks Using a PKM | InTechOpen, Published on: 2010-03-01. Authors: A. Traslosheros, L. Angel, J. M. Sebastian, et