International Conference on Computer and Knowledge Engineering

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Real-time Implementation of Fuzzy Visual Servoing for a Delta Robot via Shape and Color Detection

Authors :

Nooshin Najafian¹ Alireza Ashrafi Majd² Abbas Ansaroudi³ Sahar Aghazadeh⁴ Manizheh Zakeri⁵ Mohammad-Reza Sayyed Noorani⁶

1- dept. Mechatronics Engineering, University of Tabriz, Tabriz, Iran 2- dept. Mechatronics Engineering, University of Tabriz, Tabriz, Iran 3- dept. Mechatronics Engineering, University of Tabriz, Tabriz, Iran 4- dept. Mechatronics Engineering, University of Tabriz, Tabriz, Iran 5- dept. Mechatronics Engineering, University of Tabriz, Tabriz, Iran 6- dept. Mechatronics Engineering, University of Tabriz, Tabriz, Iran

Keywords :

Delta robot،visual servoing،inverse kinematics،fuzzy inference system،real-time implementation

Abstract :

Visual servoing is an essential part of modern control strategies to have intelligent robots. In fact, a camera can be used instead of many sensors that required for acquiring feedback information. Delta robots are parallel robots with three degrees of freedom (DoFs), commonly used for high-speed pick-and-place tasks. In this paper, we address visual servoing for a Delta robot based on detecting the shape and color cues of the robot’s end-effector and target object. The position of both of them are recognized via image processing, step by step, and then by solving the inverse kinematics problem, the end effector is conducted to approach the target. This procedure is adopted by a fuzzy inference system that controls the approaching steps based on the distance to the target. This idea was implemented in a real-time protocol and its success is verified experimentally. This setup provides a foundation for future applications in learning-based robotic control systems.