Fuzzy controlled color-based object sorter using robotic arm with machine vision

Date of Publication

2016

Document Type

Bachelor's Thesis

Degree Name

Bachelor of Science in Computer Engineering

College

Gokongwei College of Engineering

Department/Unit

Electronics and Communications Engineering

Thesis Adviser

Alexander C. Abad

Defense Panel Member

Noriel C. Mallari
Argel A. Bandala

Abstract/Summary

Robotic arms are employed to assembly lines to increase productivity, efficiency and at the same time improve the quality of products. In this study, the main focus will be the development of a robotic arm designed for sorting of color-coded objects autonomously into desired locations as set by the user.

The robotic arm is a 4-DOF M100RAK robotic arm coupled with 2_DOF gripper whose movement is controlled by the implemented fuzzy logic-based joint controller (FLJC). The machine vision system is implemented using Kinect camera and Processing software to identify the coordinates of the gripper and target objects. The machine vision system together with the MPU6050 (gyro-accelerometer) sensors provides the inputs to FLJC. The FLJC computes the required joint angles and are transmitted to Arduino microcontroller for servo control.

The robotic arm's movement is tested by its accuracy of picking up target object as well as placement time the machine vision system by its accuracy of locating the gripper and target objects. The test results indicate that the success rate of picking up of objects is about 76% with a placement time on average of 50 seconds and the machine vision system is capable of determining the objects' position within 2 centimeter accuracy.

Abstract Format

html

Language

English

Format

Print

Accession Number

TU17036

Shelf Location

Archives, The Learning Commons, 12F, Henry Sy Sr. Hall

Physical Description

xiv, 242 leaves : illustrations (some color) ; 28 cm. + 1 disc ; 4 3/4 in.

Keywords

Robotics; Machine theory

This document is currently not available here.

Share

COinS