Abstract
This paper presents a predictive control strategy for an image-based visual servoing scheme that employs evolutionary optimization. The visual control task is approached as a nonlinear optimization problem that naturally handles relevant visual servoing constraints such as workspace limitations and visibility restrictions. As the predictive scheme requires a reliable model, this paper uses a local model that is based on the visual interaction matrix and a global model that employs 3D trajectory data extracted from a quaternion-based interpolator. The work assumes a free-flying camera with 6-DOF simulation whose results support the discussion on the constraint handling and the image prediction scheme.
Highlights
Past decades have witnessed the extensive development of the visual servoing (VS) control
The spherical interpolation is incorporated into the predictive control strategy as the model guiding the BAT optimization algorithm
This research has demonstrated the usefulness of a predictive control strategy for an image-based visual servoing scheme that employs an evolutionary optimization algorithm to improve the performance of the servoing task
Summary
Past decades have witnessed the extensive development of the visual servoing (VS) control. A local model uses the classic image Jacobian matrix while a second test uses a quaternion-based 3D trajectory generator As it will be carefully discussed, the optimization algorithm uses prediction to improve the overall visual servoing performance by means of a predictive control structure that has been designed to fit within the visual control scheme. Just as it has been widely demonstrated, the use of optimization within the visual servoing control scheme has delivered some relevant contributions in particular for the image-based schemes that naturally handle the most important visual constraints at the same time control signals are generated with remarkable examples being found in [12, 15,16,17] All these solutions use classic optimization methods in order to minimize an objective function since the goal of an optimization scheme is to find an acceptable solution of a given objective function that is defined over a given search space; novel methods that are known as Evolutionary Methods have been proposed as a handy alternative.
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