Robotic Arm Guided by Deep Neural Networks and ew Knowledge-Based Edge Detector for Pick and Place Applications
Küçük Resim Yok
Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This paper presents the preliminary results on the robotic handling for industrial products with various geometric shapes. The main contribution of the present study is to two-fold: the first one is to set up a robotic arm for pick-and-place operation, along with all necessary inverse-kinematics and simulation environment setting, and the second one is to propose a new edge detection approach, which produces robust training patterns and also able to precisely determine the center of mass of the objects. The new edge detection relies on the knowledge-based rules, which emphasize the neighboring pixels on the edge. A deep learning classifier is trained using a dataset which consists of the edge information of different shapes of the objects with diverse orientations and illumination. The preliminary results show that the method is helpful in recognizing the objects correctly and does not be affected by illumination and orientation. After successful recognition, the center of the object is being extracted and the information is passed to a micro-controller which guides robotic arm for a pick-and-place operation of the objects. © 2021 IEEE.
Açıklama
Kocaeli University; Kocaeli University Technopark
2021 International Conference on INnovations in Intelligent SysTems and Applications, INISTA 2021 -- 25 August 2021 through 27 August 2021 -- Kocaeli -- 172175
2021 International Conference on INnovations in Intelligent SysTems and Applications, INISTA 2021 -- 25 August 2021 through 27 August 2021 -- Kocaeli -- 172175
Anahtar Kelimeler
Deep learning, Edge detection, Industrial Robots, Knowledge based rules, Object detection, Robotic arm
Kaynak
2021 International Conference on INnovations in Intelligent SysTems and Applications, INISTA 2021 - Proceedings
WoS Q Değeri
Scopus Q Değeri
N/A
