Robust online model predictive control for image-based visual servoing in polar coordinates

Abstract

In this paper, a novel robust online model predictive control (RMPC) method for image-based visual servoing (IBVS) in polar coordinates is proposed. First, the Jacobian matrix is transformed into a weighted combination of vertex matrices of convex polytopic by tensor product (TP) model transformation method. Then, a new IBVS control design condition for 6-DOF manipulator submitting to robot physical limitations and visibility constraints is obtained in polar coordinates by using RMPC technique. The optimal value of the control signal can be solved online when carrying out the convex optimization problem. The proposed control strategy can effectively improve the trajectory in the case that involves translation and rotation with fast response while averting the pseudo-inverse of the image Jacobian matrix. Conclusively, the effectiveness of the proposed scheme is validated by simulations and experiments on a 6-DOF manipulator.