Augmented Reality (AR) has a number of applications in industry, but remote assistance represents one of the most prominent and widely studied use cases. Notwithstanding, although the set of functionalities supporting the communication between remote experts and on-site operators grew over time, the way in which remote assistance is delivered has not evolved yet to unleash the full potential of AR technology. The expert typically guides the operator step-by-step, and basically uses AR-based hints to visually support voice instructions. With this approach, skilled human resources may go under-utilized, as the time an expert invests in the assistance corresponds to the time needed by the operator to execute the requested operations. The goal of this work is to introduce a new approach to remote assistance that takes advantage of AR functionalities separately proposed in academic works and commercial products to re-organize the guidance workflow, with the aim to increase the operator's autonomy and, thus, optimize the use of expert's time. An AR-powered remote assistance platform able to support the devised approach is also presented. By means of a user study, this approach was compared to traditional step-by-step guidance, with the aim to estimate what is the potential of AR that is still unexploited. Results showed that with the new approach it is possible to reduce the time investment for the expert, allowing the operator to autonomously complete the assigned tasks in a time comparable to step-by-step guidance with a negligible need for further support.

Improving AR-powered remote assistance: A new approach aimed to foster operator’s autonomy and optimize the use of skilled resources / Calandra, Davide; Cannavò, Alberto; Lamberti, Fabrizio. - In: THE INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY. - ISSN 1433-3015. - STAMPA. - 114:(2021), pp. 3147-3164. [10.1007/s00170-021-06871-4]

Improving AR-powered remote assistance: A new approach aimed to foster operator’s autonomy and optimize the use of skilled resources

Calandra, Davide;Cannavò, Alberto;Lamberti, Fabrizio
2021

Abstract

Augmented Reality (AR) has a number of applications in industry, but remote assistance represents one of the most prominent and widely studied use cases. Notwithstanding, although the set of functionalities supporting the communication between remote experts and on-site operators grew over time, the way in which remote assistance is delivered has not evolved yet to unleash the full potential of AR technology. The expert typically guides the operator step-by-step, and basically uses AR-based hints to visually support voice instructions. With this approach, skilled human resources may go under-utilized, as the time an expert invests in the assistance corresponds to the time needed by the operator to execute the requested operations. The goal of this work is to introduce a new approach to remote assistance that takes advantage of AR functionalities separately proposed in academic works and commercial products to re-organize the guidance workflow, with the aim to increase the operator's autonomy and, thus, optimize the use of expert's time. An AR-powered remote assistance platform able to support the devised approach is also presented. By means of a user study, this approach was compared to traditional step-by-step guidance, with the aim to estimate what is the potential of AR that is still unexploited. Results showed that with the new approach it is possible to reduce the time investment for the expert, allowing the operator to autonomously complete the assigned tasks in a time comparable to step-by-step guidance with a negligible need for further support.
File in questo prodotto:
File Dimensione Formato  
____published_redowloaded_final_Calandra2021_Article_ImprovingAR-poweredRemoteAssis.pdf

accesso aperto

Descrizione: Post-print versione editoriale
Tipologia: 2a Post-print versione editoriale / Version of Record
Licenza: Creative commons
Dimensione 2.85 MB
Formato Adobe PDF
2.85 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

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/11583/2873218