Robot Guidance Using Machine Vision Techniques in Industrial Environments: A Comparative Review

In the factory of the future, most of the operations will be done by autonomous robots that need visual feedback to move around the working space avoiding obstacles, to work collaboratively with humans, to identify and locate the working parts, to complete the information provided by other sensors t...

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Main Authors: Luis Pérez, Íñigo Rodríguez, Nuria Rodríguez, Rubén Usamentiaga, Daniel F. García
Format: Article
Language:English
Published: MDPI AG 2016-03-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/16/3/335
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spelling doaj-cbe03fbed8224196a265c1bfa372f4562020-11-25T01:01:00ZengMDPI AGSensors1424-82202016-03-0116333510.3390/s16030335s16030335Robot Guidance Using Machine Vision Techniques in Industrial Environments: A Comparative ReviewLuis Pérez0Íñigo Rodríguez1Nuria Rodríguez2Rubén Usamentiaga3Daniel F. García4Fundación PRODINTEC, Avda. Jardín Botánico 1345, 33203 Gijón (Asturias), SpainFundación PRODINTEC, Avda. Jardín Botánico 1345, 33203 Gijón (Asturias), SpainFundación PRODINTEC, Avda. Jardín Botánico 1345, 33203 Gijón (Asturias), SpainDepartment of Computer Science and Engineering, Universidad de Oviedo, Campus de Viesques, 33203 Gijón (Asturias), SpainDepartment of Computer Science and Engineering, Universidad de Oviedo, Campus de Viesques, 33203 Gijón (Asturias), SpainIn the factory of the future, most of the operations will be done by autonomous robots that need visual feedback to move around the working space avoiding obstacles, to work collaboratively with humans, to identify and locate the working parts, to complete the information provided by other sensors to improve their positioning accuracy, etc. Different vision techniques, such as photogrammetry, stereo vision, structured light, time of flight and laser triangulation, among others, are widely used for inspection and quality control processes in the industry and now for robot guidance. Choosing which type of vision system to use is highly dependent on the parts that need to be located or measured. Thus, in this paper a comparative review of different machine vision techniques for robot guidance is presented. This work analyzes accuracy, range and weight of the sensors, safety, processing time and environmental influences. Researchers and developers can take it as a background information for their future works.http://www.mdpi.com/1424-8220/16/3/335machine vision3D sensorsperception for manipulationrobot guidancerobot posepart localization
collection DOAJ
language English
format Article
sources DOAJ
author Luis Pérez
Íñigo Rodríguez
Nuria Rodríguez
Rubén Usamentiaga
Daniel F. García
spellingShingle Luis Pérez
Íñigo Rodríguez
Nuria Rodríguez
Rubén Usamentiaga
Daniel F. García
Robot Guidance Using Machine Vision Techniques in Industrial Environments: A Comparative Review
Sensors
machine vision
3D sensors
perception for manipulation
robot guidance
robot pose
part localization
author_facet Luis Pérez
Íñigo Rodríguez
Nuria Rodríguez
Rubén Usamentiaga
Daniel F. García
author_sort Luis Pérez
title Robot Guidance Using Machine Vision Techniques in Industrial Environments: A Comparative Review
title_short Robot Guidance Using Machine Vision Techniques in Industrial Environments: A Comparative Review
title_full Robot Guidance Using Machine Vision Techniques in Industrial Environments: A Comparative Review
title_fullStr Robot Guidance Using Machine Vision Techniques in Industrial Environments: A Comparative Review
title_full_unstemmed Robot Guidance Using Machine Vision Techniques in Industrial Environments: A Comparative Review
title_sort robot guidance using machine vision techniques in industrial environments: a comparative review
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2016-03-01
description In the factory of the future, most of the operations will be done by autonomous robots that need visual feedback to move around the working space avoiding obstacles, to work collaboratively with humans, to identify and locate the working parts, to complete the information provided by other sensors to improve their positioning accuracy, etc. Different vision techniques, such as photogrammetry, stereo vision, structured light, time of flight and laser triangulation, among others, are widely used for inspection and quality control processes in the industry and now for robot guidance. Choosing which type of vision system to use is highly dependent on the parts that need to be located or measured. Thus, in this paper a comparative review of different machine vision techniques for robot guidance is presented. This work analyzes accuracy, range and weight of the sensors, safety, processing time and environmental influences. Researchers and developers can take it as a background information for their future works.
topic machine vision
3D sensors
perception for manipulation
robot guidance
robot pose
part localization
url http://www.mdpi.com/1424-8220/16/3/335
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