In this work, a new 2D adaptive visual positioning/tracking controller is considered. The proposed scheme is developed for image-based eye-to-hand systems to perform position and tracking tasks on the 3D environment, when both camera calibration and robot parameters are uncertain. The symmetric-diagonal-upper (SDU) factorization method is adopted to solve the adaptive multivariable control problem. The positioning/tracking controller is first developed for the Cartesian robot case, and then extended to the general robotic system. Simulation results are also presented for the proposed strategy.

A control-theoretical solution is presented for the direct adaptive visual control of planar manipulators using a fixed camera, when both camera calibration and robot dynamics are uncertain. The proposed scheme is developed for image-based look-and-move visual systems to allow tracking of a moving target. In order to solve the multivariable parameter adaptive problem, the proposed immersion and invariance (I&I) method is used. The scheme is then combined with the adaptive controller for the manipulator, taking into account its nonlinear dynamics and leading to an overall stable adaptive visual system. Simulations and experimental results are also presented for the proposed strategy.