In this work, we present a vision system particularly suited to the automatic recognition of reels in the field of automatic packaging machines. The output of the vision system is used to guide the autonomous grasping of the reels by a robot for a subsequent manipulation task. The proposed solution is built around three different methods to solve the ellipse-detection problem in an image. Such methods leverage standard image processing and mathematical algorithms, which are tailored to the targeted application. An experimental campaign demonstrates the efficacy of the proposed approach, even in the presence of low computational power and limited hardware resources, as in the use-case at hand.

Comari S., Carricato M. (2022). Vision-Based Robotic Grasping of Reels for Automatic Packaging Machines. APPLIED SCIENCES, 12(15), 1-18 [10.3390/app12157835].

Vision-Based Robotic Grasping of Reels for Automatic Packaging Machines

Comari S.;Carricato M.
2022

Abstract

In this work, we present a vision system particularly suited to the automatic recognition of reels in the field of automatic packaging machines. The output of the vision system is used to guide the autonomous grasping of the reels by a robot for a subsequent manipulation task. The proposed solution is built around three different methods to solve the ellipse-detection problem in an image. Such methods leverage standard image processing and mathematical algorithms, which are tailored to the targeted application. An experimental campaign demonstrates the efficacy of the proposed approach, even in the presence of low computational power and limited hardware resources, as in the use-case at hand.
2022
Comari S., Carricato M. (2022). Vision-Based Robotic Grasping of Reels for Automatic Packaging Machines. APPLIED SCIENCES, 12(15), 1-18 [10.3390/app12157835].
Comari S.; Carricato M.
File in questo prodotto:
File Dimensione Formato  
Comari-Carricato_APPLSCI2022_Published_reduced.pdf

accesso aperto

Descrizione: Full-text paper
Tipo: Versione (PDF) editoriale
Licenza: Creative commons
Dimensione 771.32 kB
Formato Adobe PDF
771.32 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/893994
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 2
social impact