Image Based Controller for Visual Servoing Systems

In this paper an image controller using model predictive control (MPC) for visual servoing systems is presented and its performances are analyzed. An eye-inhand type servoing architecture, composed from a 6 degree of freedom robot and a camera mounted on the gripper is considered. Modeling the visual servo open loop is composed from two stages: first the designing of a model for dynamics of the velocity controlled robot and second a model of the visual sensor. In classical approach, an image interaction matrix maps image space errors into errors in Cartesian space. For the MPC approach, using the open loop visual servo model, an image based predictor is developed. The image based predictor generates the future trajectories of a visual feature ensemble when past and future camera velocities are known. In order to obtain better performances for visual servoing systems an advanced technique is required, for this mater using the developed predictor an image based predictive controller (IbPC) is designed. Implementation, tests and validation of IbPC are conducted and performances in an image based visual servoing scheme are revealed in comparison with a PI image based controller. Experimental results underline the better performances of IbPC as an evaluation regarding the performances of PI classical approach.