Adaptive motion control of manipulators with uncalibrated visual feedback

Abstract

For the visual servoing tasks, it is required to calibrate accurately the homogeneous transformation matrix between the robot base frame and vision frame besides the intrinsic parameters of the vision system. In this paper, based on an important observation, that is, the unknown transformation matrix between the robot base frame and vision frame can be separated from the visual Jacobian matrix, and by virtue of decomposition of rotation matrix, we design a novel adaptive position-based visual servo controller for manipulators when the transformation matrix is not calibrated. It is proved with a full dynamics of the system by the Lyapunov approach that the motion of the manipulator approaches asymptotically to the desired trajectory. Simulations and experimental results both demonstrate the performance of this new controller.