Visual Servoing of Robot Manipulators Using Model-based Predictive Control

In this paper, a model predictive control strategy is presented to visual servoing a robot manipulator with eye-in-hand configuration. Starting with the discrete form of the time derivative of features related with camera velocity through image Jacobian matrix and taking into account the discrete robot model, a new approach for computing the predictions is introduced. By means of a cost function based on errors in image plane, convergence of robot motion has been obtained through nonlinear constraint optimization, which takes into consideration the visibility loss of features due to camera motion. Using a visual servoing simulator, the predictive strategy was successfully tested.