Nonlinear model predictive control for visual servoing from a set of points

From a set of points in the image plane, six independent image features are designed with nice decoupling and linear properties. Then, nonlinear model predictive control is used to redefine the visual servoing as a constrained optimization problem, where local predictive model is designed based on image jacobian. The necessarity of field-of-view constraint is deceased, thanks to proposed strategy for recovery of disappearing matched point features by projection homography. This helps to reduce the unknown parameters in the optimization problem. On the other hand, proposed constrained visual servoing control is expected to perform well in task space because of selected features. Finally, simulation results are presented to illustrate the effectiveness and improved performance of proposed method.

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