A dynamic Jacobian estimation method for uncalibrated visual servoing

Abstract

A dynamic Broyden's method is presented for use in a quasi-Newton control scheme for model-independent vision guided robotic control. Model independent visual servo control is defined as using visual feedback to control a robot without precisely calibrated kinematic and camera models. The control problem is formulated as a nonlinear least squares optimization. For the moving target case, this results in a time-varying objective function which is minimized using a dynamic Newton's method. The dynamic Jacobian estimation scheme is used to estimate the combined robot and image Jacobians. Experimental results for a two-degree-of-freedom system demonstrates the success of the algorithm.