Adaptive 2.5D visual servoing of cartesian robots

In this paper, the 3-dimensional (3D) position of a camera held by the end-effector of a cartesian robot manipulator is regulated to a constant desired position despite (i) the lack of depth information of the actual or desired camera position from a target, (ii) the lack of a 3D model of the target object, and (iii) the lack of information of intrinsic and extrinsic camera calibration matrices. Specifically, by fusing 2D image-space and 3D task-space information (i.e., 2.5D visual servoing), an adaptive controller is developed that is proven to ensure asymptotic position regulation of the cartesian robot. The stability of the proposed controller is proven through a rigorous Lyapunov-based stability analysis.