Visual predictive control from distance-based and Homography-based Features
This paper deals with image based visual servoing (IBSV) by a visual predictive control (VPC) approach. Based on nonlinear model predictive control (NMPC), the visual servoing problem is formulated into a nonlinear constrained minimization problem in the image plane. A global model describing the behavior of the robotic system equipped with the camera is used to predict the evolution of the visual feature on a future horizon. The main interest of this method is the capability to easily take into account different constraints like mechanical limitations and/or visibility constraints. Simulation experiments are performed on a planar manipulator with an omnidirectional camera. Comparisons with the classical control law based on the interaction matrix highlight the efficiency and the robustness of the proposed approach, especially in difficult initial configurations and large displacements.