Mr. Gyu-Jong Choi Profile

Gyu-Jong Choi

at Pukyong National Univ

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Proceedings Article | 5 October 2001 Paper

Visual servoing system based on ANFIS (adaptive neuro fuzzy inference system)

Gyu-Jong Choi, Kyoung-Soo Lee, Doo-Sung Ahn

Proceedings Volume 4572, (2001) https://doi.org/10.1117/12.444185

KEYWORDS: Visualization, Data acquisition, Fuzzy systems, Cameras, Fuzzy logic, Detection and tracking algorithms, Control systems, Kinematics, Neural networks, Servomechanisms

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Research in this visual servoing field in the past few decades has produced remarkable results, leading to many exciting expectations as well as new challenges. However, because of the complicated calculation of the inverse Jacobian, it is difficult to implement in real time. Therefore, instead of using the inverse Jacobian, this paper employs the ANFIS (Adaptive Neuro Fuzzy Inference System) approach for visual servo control of a robot manipulator. It is based on visual feedback and no prior information about the kinematics of robot and the camera calibration are unnecessary. Firstly, to efficiently control a manipulator, 3D space is divided into two 2D spaces. And then, we acquire training data from each 2D space and ANFIS is learned by the training data. We categorize the robot movement into two kinds of actions. That is, TOWARD action is performed, in the xy plane, by joint 1 and APPROACH action is performed, in the plane orthogonal to the xy plane, by joint 2 and joint 3. The time varying object can be tracked by controlling both actions in each plane and the simulation results show the validation of our approach.

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