Fuzzy model based control applied to image-based visual servoing

A new approach to eye-in-hand image-based visual servoing based on fuzzy modeling and control is proposed in this paper. Fuzzy modeling is applied to obtain an inverse model of the mapping between image features velocities and joints velocities, avoiding the necessity of inverting the Jacobian. An inverse model is identified for each trajectory using measurements data of a robotic manipulator, and it is directly used as a controller. As the inversion is not exact, steady-state errors must be compensated. This paper proposes the use of a fuzzy compensator to deal with this problem. The control scheme contains an inverse fuzzy model and a fuzzy compensator, which are applied to a robotic manipulator performing visual servoing, for a given profile of image features velocities. The obtained results show the effectiveness of the proposed control scheme: the fuzzy controller can follow a point-to-point pre-defined trajectory faster (or smoother) than the classic approach.