Real-time visual predictive controller for image-based trajectory tracking of a mobile robot

This paper deals with the design of a real-time controller for trajectory tracking in the image plane. The Image-Based Visual Servoing (IBVS) task is addressed by a visual predictive approach. The trajectory tracking is formulated into a nonlinear optimization problem in the image plane. The unavoidable constraints in experiments are easily taken into account in the design of the predictive control law. The global model, combining the mobile robot and camera model, is used to predict the behavior of the process. The flatness property of this global model is proved in the general case, that is whatever the camera posture. The flat model permits to reduce the computational time by a factor 2. Experiments are performed on a non holonomic mobile robot with a deported perspective camera. Experimental results show the efficiency and the robustness of the real-time control approach. Visibility constraints are added to point out the capability of the control to avoid obstacles.