Uncalibrated Visual Tracking Control Without Visual Velocity

This paper presents a new adaptive controller for image-based tracking of a robot manipulator without using visual velocity when the intrinsic and extrinsic parameters of the camera are not calibrated. Most of existing controllers require the measurement of the visual velocity, which is subject to big noises in general due to low sampling rates of the vision loop. To avoid performance decaying caused by measurement errors of the visual velocity we propose a new image-based tracking controller based on the proposal of an estimator of visual velocity. With a full consideration of dynamic responses of the robot manipulator, we proved the convergence of the image errors of the trajectory to zero and the convergence of the estimated parameters to the real values up to a scale by the Lyapunov method. Experiments have been conducted to demonstrate good convergence of the trajectory errors under the control of the proposed method.