<title>Experimental results using vision-based control for uncalibrated robotic systems</title>

Abstract

This work demonstrates a vision-based control technique that does not require robot or vision system calibration. There are two distinct advantages: first, the approach is generic and can be applied to a variety of systems; second, calibration is unnecessary after a reconfiguration or disturbance to the robotic workcell. It has the potential to provide a low-cost, low-maintenance automation solution for unstructured industries and environments. The robot end- effector tracks a moving target using a novel dynamic quasi- Newton control was formulated in the image plane and on-line Jacobian estimation using either a dynamic Broyden's method or a dynamic recursive least squares algorithm. Experimental results demonstrate convergent and stable control of an uncalibrated manipulator tracking a moving target. The method is shown to be robust to system reconfiguration such as modifications to the position and orientation of the camera.