Performing stable 2D adaptive visual positioning/tracking control without explicit depth measurement

Abstract

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.