Abstract
Advanced techniques like image based predictive control are embedded now in visual servoing applications. As it can be seen in literature, the main visual features used in the nonlinear predictive servoing architecture are point features. In order to increase performances of the visual servoing systems, a model predictive controller based on image moments derived from point features is proposed in this paper. The new predictive control technique uses a local model based predictor for image moments and a reference trajectory in order to ensure a robust behavior. Based on the new predictive control strategy, a visual control architecture is designed and a simulator is developed. Simulation results are obtained for a visual sensor attached to a 6 d.o.f. robot manipulator in an eye-in-hand configuration. The results revealed high efficiency and robustness for the proposed approach.
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Copot, C., Lazar, C., Burlacu, A. (2013). Nonlinear Model Based Predictive Control of Visual Servoing Systems Using Image Moments. In: Dumitrache, L. (eds) Advances in Intelligent Control Systems and Computer Science. Advances in Intelligent Systems and Computing, vol 187. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32548-9_9
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DOI: https://doi.org/10.1007/978-3-642-32548-9_9
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