Human-machine collaboration is a key aspect in modern industries, which must be compliant to the Industry 4.0 paradigm. Although the collaboration can be achieved using a Collaborative Robot in a purposely designed workstation, this solution is not always neither feasible nor affordable for the specific task to be carried out in the workstation. On the other hand, using a smart HMI to make an industrial robot a “smart” robot can be a better and affordable solution depending on the task. In this work we present the preliminary development and characteristics of an experimental HMI for smart manufacturing developed in MATLAB and ROS Industrial. The collaboration between humans and robots is achieved by leveraging the Faster R-CNN Object Detector to robustly detect and recognize the hand gestures performed in real-time. The system is based on a state machine to carry out simple tasks such as the repeated movement of the robot following a given trajectory and a pick and place task where the robot interactively reaches a given point and a jog modality.

Hand Gesture Recognition for Collaborative Workstations: A Smart Command System Prototype

Nuzzi, Cristina
Investigation
;
Pasinetti, Simone
Membro del Collaboration Group
;
PAGANI, ROBERTO
Membro del Collaboration Group
;
Docchio, Franco
Membro del Collaboration Group
;
Sansoni, Giovanna
Supervision
2019-01-01

Abstract

Human-machine collaboration is a key aspect in modern industries, which must be compliant to the Industry 4.0 paradigm. Although the collaboration can be achieved using a Collaborative Robot in a purposely designed workstation, this solution is not always neither feasible nor affordable for the specific task to be carried out in the workstation. On the other hand, using a smart HMI to make an industrial robot a “smart” robot can be a better and affordable solution depending on the task. In this work we present the preliminary development and characteristics of an experimental HMI for smart manufacturing developed in MATLAB and ROS Industrial. The collaboration between humans and robots is achieved by leveraging the Faster R-CNN Object Detector to robustly detect and recognize the hand gestures performed in real-time. The system is based on a state machine to carry out simple tasks such as the repeated movement of the robot following a given trajectory and a pick and place task where the robot interactively reaches a given point and a jog modality.
2019
978-3-030-30753-0
978-3-030-30754-7
File in questo prodotto:
File Dimensione Formato  
2019_Hand gesture recognition for collaborative workstations a smart command system prototype.pdf

gestori archivio

Tipologia: Documento in Post-print
Licenza: NON PUBBLICO - Accesso privato/ristretto
Dimensione 469.43 kB
Formato Adobe PDF
469.43 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

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/11379/525594
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 9
  • ???jsp.display-item.citation.isi??? ND
social impact