Volume 27 Issue 10 - Publication Date: 1 October 2008
Feature Depth Observation for Image-based Visual Servoing: Theory and Experiments
A. De Luca, G. Oriolo, and P. Robuffo Giordano Dipartimento di Informatica e Sistemistica, Università di Roma “La Sapienza”, Via Ariosto 25, 00185 Roma, Italy
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 required for 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.
Multimedia Key
= Video = Data = Code = Image
Example 1: The video shows the external and camera views of the experiment described in Section 7.3, Figure 16(d). The depth observer is initialized with a value of 8 m, while the robot starts at about 4 m from the target. 4.71MB (avi)
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