Abstract
This paper presents a distributed fuzzy proportional control system for a vision guided redundant robot manipulator. Firstly, the Takagi Sugeno (TS) fuzzy algorithm is used to model analytical Image Based Visual Servoing (IBVS) using shape moments by offline learning. This control method is applied to an uncalibrated robotic system with eye-in-hand visual feedback. The system is able to track a moving object through a variety of motions and maintain the object's image features in a desired position in the image plane without a priori knowledge of the robot kinematic, camera calibration and inverse Jacobian. The experimental results of both static and moving targets using the 7 DOF PowerCube manipulator from Amtec Robotic show and verify its performance in a realtime application.
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