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...
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2016-03-01
|
Series: | Sensors |
Subjects: | |
Online Access: | http://www.mdpi.com/1424-8220/16/3/335 |
id |
doaj-cbe03fbed8224196a265c1bfa372f456 |
---|---|
record_format |
Article |
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 |
work_keys_str_mv |
AT luisperez robotguidanceusingmachinevisiontechniquesinindustrialenvironmentsacomparativereview AT inigorodriguez robotguidanceusingmachinevisiontechniquesinindustrialenvironmentsacomparativereview AT nuriarodriguez robotguidanceusingmachinevisiontechniquesinindustrialenvironmentsacomparativereview AT rubenusamentiaga robotguidanceusingmachinevisiontechniquesinindustrialenvironmentsacomparativereview AT danielfgarcia robotguidanceusingmachinevisiontechniquesinindustrialenvironmentsacomparativereview |
_version_ |
1725211425365819392 |