Visual servoing control of robot manipulator in 3D space using fuzzy hybrid controller

In this paper a new visual servoing control for robot manipulator in 3D space is presented. In traditional visual servoing control, models of robot and camera are needed. Obtaining these models are time consuming and sometimes impossible. In addition, Jacobean matrix has an important role on visual servoing. Calculating this matrix and its inverse (if exists) in each step-time of control process is complicated. Here, we use intelligent methods to cope with the above challenges. A hybrid fuzzy controller is proposed to control robot manipulator. Visual inputs of the controller are provided by Kinect and the outputs are the rotation of joints motors. The first controller in based on fuzzy inverse model which approximates real inverse model of robot using gathered data. In order to increase accuracy a second fuzzy controller is used, which is designed by expert knowledge. The output of this controller suppresses the first controller output where the end-effector is in the predefined near-goal area. The proposed method is applied to control a real robot manipulator (ARM_6Ax18). Experimental results show that by using the proposed method in practice, the end-effector reaches from any random start position to the goal position with a good accuracy in robot workspace.