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A. De Luca, G. Oriolo, P. Robuffo Giordano. Feature Depth Observation for Image-based Visual Servoing: Theory and Experiments. The International Journal of Robotics Research, 27(10):1093-1116, October 2008.

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In the classical image-based visual servoing framework, error signals are directly computed from image feature parameters, allowing, in principle, control schemes to be obtained that need neither a complete three-dimensional (3D) model of the scene nor a perfect camera calibration. However, when the computation of control signals involves the interaction matrix, the current value of some 3D parameters is requiredfor each considered feature, and typically a rough approximation of this value is used. With reference to the case of a point feature, for which the relevant 3D parameter is the depth Z, we propose a visual servoing approach where Z is observed and made available for servoing. This is achieved by interpreting depth as an unmeasurable state with known dynamics, and by building a non-linear observer that asymptotically recovers the actual value of Z for the selected feature. A byproduct of our analysis is the rigorous characterization of camera motions that actually allow such observation. Moreover, in the case of a partially uncalibrated camera, it is possible to exploit complementary camera motions in order to preliminarily estimate the focal length without knowing Z. Simulations and experimental results are presented for a mobile robot with an on-board camera in order to illustrate the benefits of integrating the depth observation within classical visual servoing schemes

BibTex Reference

   Author = {De Luca, A. and Oriolo, G. and Robuffo Giordano, P.},
   Title = {{Feature Depth Observation for Image-based Visual Servoing: Theory and Experiments}},
   Journal = {The International Journal of Robotics Research},
   Volume = {    27},
   Number = {10},
   Pages = {1093--1116},
   Month = {October},
   Year = {2008}

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