Scopus Eşleşmesi Bulundu
5
Atıf
21
Cilt
335-343
Sayfa
Scopus Yazarları: Kursad Ucar, Hasan Erdinc Kocer
Özet
In any task, robot arms can work more effectively without human control. With components such as imaging devices, it is possible to program robots to control autonomously. In this study, the problem of grasping moving objects with the robot arm is realized fully automatically. Deep learning-based You Only Look Once(YOLO) recognizes the objects moving at unknown speeds on a conveyor belt. The velocities of the detected objects are calculated by image processing methods with 2D camera frames. An Artificial Neural Network (ANN) was trained to output the angles required for the robot arm to grasp. According to the got values, the robot arm waits for the object to arrive and then realizes the grip. In the trials, the robot arm achieved successful gripping of over 93% without knowing the sizes, speeds, and positions of the objects.
Anahtar Kelimeler (Scopus)
Grasping
Kinematics
Learning and Adaptive Systems
Recognition.
Anahtar Kelimeler
Grasping
Kinematics
Learning and Adaptive Systems
Recognition.
Makale Bilgileri
Dergi
IEEE Latin America Transactions
ISSN
1548-0992
Yıl
2023
/ 2. ay
Cilt / Sayı
21
/ 2
Sayfalar
335 – 343
Makale Türü
Özgün Makale
Hakemlik
Hakemli
Endeks
SCI-Expanded
JCR Quartile
Q4
TEŞV Puanı
36,00
Yayın Dili
Türkçe
Kapsam
Uluslararası
Toplam Yazar
2 kişi
Erişim Türü
Basılı+Elektronik
Erişim Linki
Makaleye Git
Alan
Mühendislik Temel Alanı
Elektrik-Elektronik ve Haberleşme Mühendisliği
Bilgisayarla Görme
Robotik
Yapay Zeka
YÖKSİS Yazar Kaydı
Yazar Adı
UÇAR KÜRŞAD, KOÇER HASAN ERDİNÇ
YÖKSİS ID
7733998
Hızlı Erişim
Metrikler
Scopus Atıf
5
JCR Quartile
Q4
TEŞV Puanı
36,00
Yazar Sayısı
2