Research of Sorting Technology Based on Industrial Robot of Machine Vision

2012 ◽  
Author(s):  
Zhenyu Liu ◽  
Bin Zhao ◽  
Haibo Zhu
Keyword(s):  
Machine Vision ◽  
Industrial Robot

Adaptive Industrial Robots Using Machine Vision

2018 ◽  
Author(s):  
Vladimir Kuts ◽  
Tauno Otto ◽  
Toivo Tähemaa ◽  
Khuldoon Bukhari ◽  
Tengiz Pataraia
Keyword(s):  
Machine Vision ◽  
Manufacturing Industry ◽  
Industrial Robot ◽  
Industrial Robots ◽  
Engineering Industry ◽  
Test Environment ◽  
Operation System ◽  
Robotic Cells ◽  
Self Learning ◽  
Human Robot Collaboration

The use of industrial robots in modern manufacturing scenarios is a rising trend in the engineering industry. Currently, industrial robots are able to perform pre-programmed tasks very efficiently irrespective of time and complexity. However, often robots encounter unknown scenarios and to solve those, they need to cooperate with humans, leading to unnecessary downtime of the machine and the need for human intervention. The main aim of this study is to propose a method to develop adaptive industrial robots using Machine Learning (ML)/Machine Vision (MV) tools. The proposed method aims to reduce the effort of re-programming and enable self-learning in industrial robots. The elaborated online programming method can lead to fully automated industrial robotic cells in accordance with the human-robot collaboration standard and provide multiple usage options of this approach in the manufacturing industry. Machine Vision (MV) tools used for online programming allow industrial robots to make autonomous decisions during sorting or assembling operations based on the color and/or shape of the test object. The test setup consisted of an industrial robot cell, cameras and LIDAR connected to MATLAB through a Robot Operation System (ROS). The online programming tests and simulations were performed using Virtual/Augmented Reality (VR/AR) toolkits together with a Digital Twin (DT) concept, to test the industrial robot program on a digital object before executing it on the real object, thus creating a safe and secure test environment.

Edible Bird Nest Processing using Machine Vision and Robotic Arm

2015 ◽  
Vol 72 (2) ◽  
Author(s):  
Yuvarajoo Subramaniam ◽  
Yeong Che Fai ◽  
Eileen Su Lee Ming
Keyword(s):  
Machine Vision ◽  
Large Scale ◽  
Vision System ◽  
Industrial Robot ◽  
Processing System ◽  
Food Product ◽  
Cost Effective ◽  
Automated System ◽  
Scale Production ◽  
Bird Nest

Edible Bird nest food product is one of the demanding food product in food production industry. Government looking into ways to improve this industry to boost the economy. Many large scale production are being operated around Malaysia. One of the major difficulties faced in processing the bird nest is to remove its impurities or more formerly known as dirt. Current conventional cleaning method which is manual cleaning is not cost effective and time consuming. Furthermore, it also requires large number of workforce to be used for processing small quantities of bird nest. This paper presents an automated system which utilizes machine vision system and an industrial robot to accomplish a better processing system for edible bird nest. This system offers great advantage compared to conventional process by reducing the time consumed for processing and increase the efficiency.

Application of Machine Vision Based on DM642 of Embedded System

2014 ◽  
Vol 701-702 ◽  
pp. 428-432
Author(s):  
Zhen Yu Liu ◽  
He Wen Xu
Keyword(s):  
Feature Extraction ◽  
Machine Vision ◽  
Embedded System ◽  
Vision System ◽  
Industrial Robot ◽  
Industrial Applications ◽  
Network Interface ◽  
Machine Vision System ◽  
Image Preprocessing ◽  
Robot Controller

This article takes the industrial robot workpiece sorting issue as a background, introduces an embedded machine vision system based on DM642. The system realizes the image preprocessing, feature extraction, image recognition and other work in DSP, and transmits detection results to robot controller through network interface. Experimental results show that the system can effectively solve the problem of sorting regular geometric workpiece, and can meet the requirements of real-time and accuracy in industrial applications.

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