Abstract
In this chapter, image-based visual servoing is addressed via nonlinear model predictive control. The visual servoing task is formulated into a nonlinear optimization problem in the image plane. The proposed approach, named visual predictive control, can easily and explicitly take into account 2D and 3D constraints. Furthermore, the image prediction over a finite prediction horizon plays a crucial role for large displacements. This image prediction is obtained thanks to a model. The choice of this model is discussed. A nonlinear global model and a local model based on the interaction matrix are considered. Advantages and drawbacks of both models are pointed out. Finally, simulations obtained with a 6 degrees of freedom (DOF) free-flying camera highlight the capabilities and the efficiency of the proposed approach by a comparison with the classical image-based visual servoing.KeywordsVisual FeatureVisual ServoingPrediction HorizonCamera FrameConstraint HandlingThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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