Global uncalibrated visual servoing for constrained robots working on an uncalibrated environments

This paper studies the open problem of uncalibrated visual servoing for constrained robots with parametric uncertainties, interacting with unknown environments. A new theoretical framework and its experimental validation are given. This approach produces global exponential convergence of the constrained visual position and the contact force between the end-effector and the unknown constrain surface. This approach is based on the formulation of the Visual Orthogonalization Principle (VOP), which, under the framework of passivity, yields a closed-loop system that fuses camera, encoder and force sensor signals. An experimental system running on Linux-RTAI OS is implemented to visually drive a constrained direct-drive robot manipulator, equipped with six axis JR3 force sensor and a FireWire CCD digital camera posed in fixed configuration. This experimental system proves the effectiveness of the proposed approach even when the robot, camera and restriction surface parameters are assumed as unknown.