dc.contributor.author | İşçimen, Bilal | |
dc.contributor.author | Atasoy, Hüseyin | |
dc.contributor.author | Kutlu, Yakup | |
dc.contributor.author | Yıldırım, Serdar | |
dc.contributor.author | Yıldırım, Esen | |
dc.date.accessioned | 12.07.201910:50:10 | |
dc.date.accessioned | 2019-07-12T22:07:40Z | |
dc.date.available | 12.07.201910:50:10 | |
dc.date.available | 2019-07-12T22:07:40Z | |
dc.date.issued | 2015 | |
dc.identifier.citation | Iscimen, B., Atasoy, H., Kutlu, Y., Yildirim, S., Yildirim, E. (2015). Smart robot arm motion using computer vision. Elektronika ir Elektrotechnika, 21 (6), pp. 3-7.
https://doi.org/10.5755/j01.eee.21.6.13749 | |
dc.identifier.issn | 1392-1215 | |
dc.identifier.uri | https://doi.org/10.5755/j01.eee.21.6.13749 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12508/926 | |
dc.description | WOS: 000367391900001 | en_US |
dc.description.abstract | In this study computer vision and robot arm are used together to design a smart robot arm system which can identify objects from images automatically and perform given tasks. A serving robot application, in which specific tableware can be identified and lifted from a table, is presented in this work. A new database was created by using images of objects used in serving a meal. This study consists of two phases: First phase includes recognition of the objects through computer vision algorithms and determining the specified objects' coordinates. Second phase is the realization of the robot arm's movement to the given coordinates. Artificial neural network is used for object recognition in this system. 98.30 % overall accuracy of recognition is achieved. Robot arm's joint angles were calculated by using coordinate dictionary for moving the arm to desired coordinates and the robot arm's movement was performed. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Kaunas University of Technology | en_US |
dc.relation.isversionof | 10.5755/j01.eee.21.6.13749 | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Classification | en_US |
dc.subject | Computer vision | en_US |
dc.subject | Robot arm | en_US |
dc.subject | Robot programming | en_US |
dc.subject.classification | Engineering | |
dc.subject.classification | Electrical & Electronic | |
dc.subject.classification | Robotic Arms | Library Administration | Gesture Recognition | |
dc.title | Smart Robot Arm Motion Using Computer Vision | en_US |
dc.type | article | en_US |
dc.relation.journal | Elektronika ir Elektrotechnika | en_US |
dc.contributor.department | Mühendislik ve Doğa Bilimleri Fakültesi -- Bilgisayar Mühendisliği Bölümü | en_US |
dc.identifier.volume | 21 | en_US |
dc.identifier.issue | 6 | en_US |
dc.identifier.startpage | 3 | en_US |
dc.identifier.endpage | 7 | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.contributor.isteauthor | İşçimen, Bilal | |
dc.contributor.isteauthor | Atasoy, Hüseyin | |
dc.contributor.isteauthor | Kutlu, Yakup | |
dc.contributor.isteauthor | Yıldırım, Serdar | |
dc.contributor.isteauthor | Yıldırım, Esen | |
dc.relation.index | Web of Science - Scopus | en_US |
dc.relation.index | Web of Science Core Collection - Science Citation Index Expanded | |