2.5D Visual Servoing of Wheeled Mobile Robots
In this paper, 2D image-space and reconstructed 3D task-space information (i.e., 2.5D visual servoing) is used to develop a kinematic controller that yields asymptotic regulation of the position/orientation of a wheeled mobile robot (WMR) system that is modeled as an underactuated "kinematic wheel" subject to nonholonomic constraints. By comparing the features of an object from a desired image to features of the object in the current image, geometric relationships are exploited to enable a Euclidean reconstruction from a homography matrix that relates the image-space feedback to the position/orientation of the WMR in a local coordinate system. To achieve the control objective, a unique strategy is employed in which the kinematic control design is based on measurable 2D image-space information and reconstructed 3D information. The control design is facilitated by performing the stability analysis in terms of the unmeasurable camera/WMR Euclidean position. In contrast to many of the previous 2.5D visual servo controllers, the kinematic control law does not depend on the numerical estimation of depth measurements. The control design is based on the nonlinear model of the vision system and the mobile robot system and is analyzed through a Lyapunov-based stability analysis.
For more information concerning this research, please refer to the following publication:
Y. Fang, D. M. Dawson, W. E. Dixon and M. S. de Queiroz, "Homography-Based Visual Servoing of Wheeled Mobile Robots", Proc. of the IEEE Conference on Decision and Control, December, 2002, to appear.