An indirect adaptive control approach to image based visual servoing for translational trajectory tracking

Abstract

In this work, we consider an image based visual servoing control problem, for uncertain robot manipulators. Visual feedback is provided by a fixed monocular camera with uncertain parameters, for the purpose of tracking translational trajectories of a spherical target. First, only the manipulator kinematic is considered, we propose an indirect adaptive control, with depth measurement done by prior knowledge of a few geometric properties, albeit with some uncertain geometric parameters. This method relies on parameterizing the image Jacobian, continuously updating an estimate of the parameters, using these parameters to construct an estimative image Jacobian matrix and using its inverse to calculate control laws. Based on a cascade structure, the proposed adaptive visual servoing is combined with an adaptive motion control strategy, extending the controller to a case that considers not only the nonlinear kinematics but also the dynamics of the robot arm. The stability and passivity properties are analyzed with Lyapunov method. Simulations and experimental results illustrate and highlight performance and feasibility of the controller proposed.