A dynamic quasi-Newton method for uncalibrated visual servoing

Abstract
Tracking of a moving target by uncalibrated model independent visual servo control is achieved by de- veloping a new \dynamic" quasi-Newton approach. Model independent visual servo control is dened as using visual feedback to control a robot without pre- cisely 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 new dynamic Newton's method. A second-order convergence rate is established, and it is shown that the standard method is not guaranteed con- vergence for a moving target. The algorithm is ex- tended to develop a dynamic Broyden update and sub- sequently a dynamic quasi-Newton method. Results for both one- and six-degree-of-freedom systems demon- strate the success of the algorithm and shows dramatic improvement over previous methods.

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