Dynamic proportional-fuzzy grip control for robot arm by two-dimensional vision sensing method

Abstract

In this study, a four-degree of freedom (4-DOF) robot arm uses an innovative two-dimensional vision sensing method to grip a moving target on a moving platform. This study utilizes forward and inverse kinematics to establish a dynamic model of the 4-DOF robot arm. A computer as a controller and a single charge-coupled device (CCD) calculates the two-dimensional vision sensing method and sends commands to an Arduino Uno microcontroller to drive the robot arm. According to simulation results of transient and steady states in MATLAB SimMechanics, the response of the dynamic proportional-fuzzy controller is better than the response of proportional–integral–derivative controller. To demonstrate a precise control of the point-contact grip, this study utilizes a ping pong ball as a target on a moving platform. Using the dynamic proportional-fuzzy controller based on the two-dimensional vision sensing method, the 4-DOF robot arm can position, grip, and carry a moving ping pong ball to a designated place in three-dimensional space, which breaks through the previous two-dimensional limitation using a single CCD. This breakthrough can reduce the weight and cost of the robot arm. Therefore, this study aims to utilize the technology to grip moving targets on a moving platform for manpower cost reduction in the industry or agriculture domain in the future.