An adaptive fuzzy system for the control of the vergence angle on a robotic head

Abstract

An important issue in realizing robots with stereo vision is the efficient control of the vergence angle. In an active robotic vision system the vergence angle along with the pan and tilt ones determines uniquely the fixation point in the 3D space. The vergence control involves the adjustment of the angle between the two cameras’ axes towards the fixation point and, therefore, it enables the robot to perceive depth and to compute obstacle maps. Vergence movement is directly related to the binocular fusion. Additionally, the decision for convergence or divergence is extracted either by motion affine models or by mathematical ones. In this paper, a new method for extracting the cameras’ movement direction is presented. The movement decision is performed by an adaptive fuzzy control system, the inputs of which are the zero-mean normalized cross correlation (ZNCC) and the depth estimations at each time step. The proposed system is assessed on a 4 d.o.f. robotic head, yet it can be utilized in any active binocular system, since it is computationally inexpensive and it is independent to a priori camera calibration.