InspectAR: An Augmented Reality Inspection Framework for Industry

Perla, Ramakrishna; Gupta, Gaurav; Hebbalaguppe, Ramya; Hassan, Ehtesham

doi:10.1109/ismar-adjunct.2016.0119

Cited by 17 publications

(9 citation statements)

References 2 publications

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“…For what it concerns contents reuse, in [35], an AR framework capable to record data about the intervention while the expert is providing instructions to the operator was presented. The serial number of the object of the assistance is recognized by scanning a QR code, so that relevant information (specifications, history of interventions, etc.)…”

Section: Related Workmentioning

confidence: 99%

“…Although wearable technologies (such as HMDs or smartglasses) may guarantee a higher degree of freedom compared to hand-held devices, previous works proved that they could introduce limitations in terms of interaction; hence, the latter solution is often preferred by the users [54]. Moreover, smartphones and tablets are much more common and wide-spread than wearable devices, and they were shown to be characterized by a higher ease of use as users are already accustomed with them [4,5,21,35]. Finally, the possibility to avoid the use of additional, expensive hardware may be a significant advantage from the viewpoint of the company offering the assistance service, which can serve a wider and more heterogeneous set of customers.…”

Section: Ar Devicesmentioning

confidence: 99%

“…Indeed, marker or, more in general, image detection can be useful in the considered context to identify known products (and their parts) when this information has been already integrated in the product itself by the manufacturer. For instance, in the developed application, OCR (optical character recognition) was used to identify, before starting the call, the product to be serviced via its product label (similarly to what was done in [35] using a QR code).…”

Section: Ar Trackingmentioning

confidence: 99%

See 2 more Smart Citations

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

Calandra

Cannavò

Lamberti

2021

Int J Adv Manuf Technol

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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.

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Section: Related Workmentioning

confidence: 99%

Section: Ar Devicesmentioning

confidence: 99%

Section: Ar Trackingmentioning

confidence: 99%

See 1 more Smart Citation

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

Calandra

Cannavò

Lamberti

2021

Int J Adv Manuf Technol

View full text Add to dashboard Cite

show abstract

“…Koch et al [15] presented a natural marker-based AR framework that can digitally support facility maintenance operators in performing on-site maintenance/inspection jobs. Perla et al [25] proposed an AR-based re-configurable inspection framework that can be used in maintenance and repair assistance in industrial inspection and automotive/avionics domain inspection. In the context of computer hardware inspection, Polvi et al [26] compared two guides based on a tablet computer: an AR interface with 3D-registered annotations and a non-AR picture interface with non-registered annotations.…”

Section: Related Workmentioning

confidence: 99%

Collaborative SLAM and AR-guided navigation for floor layout inspection

Ahn

Lee

et al. 2020

Vis Comput

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This paper presents how visual SLAM and AR interfaces are integrated for inspecting the floor layouts, which is a standard stage in building a semiconductor fabrication plant (commonly called a fab). The proposed system supports multiple inspectors working in a large fab floor through client-server communications. The inspectors/clients scan the fab floor using smartphones to construct the floor map collaboratively, and then, its discrepancy from the given floor plan is checked by the server. The inspection results are broadcast to all clients and visualized via AR to help the inspectors move to unscanned areas. The experiments made with the proposed system show its accuracy and efficiency. By solving a real-world industrial problem, the proposed system proves the benefits that can be brought by integrating collaborative SLAM technique and AR-guided navigation interface.

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“…To achieve this goal, the inspection procedure will involve an organized examination of a particular device. AR is regarded as a promising technology to set up the inspection process [15][16][17][18]. Another inspection application involves the patrol inspection of the running machine.…”

Section: Introductionmentioning

confidence: 99%

A Multi-User Collaborative AR System for Industrial Applications

Wang

2022

Sensors

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Augmented reality (AR) applications are increasingly being used in various fields (e.g., design, maintenance, assembly, repair, training, etc.), as AR techniques help improve efficiency and reduce costs. Moreover, collaborative AR systems extend applicability, allowing for collaborative environments for different roles. In this paper, we propose a multi-user collaborative AR system (aptly called the “multi-user collaborative system”, or MUCSys); it is composed of three ends—MUCStudio, MUCView, and MUCServer. MUCStudio aims to construct industrial content with CAD model transformation, simplification, database update, marker design, scene editing, and exportation, while MUCView contains sensor data analysis, real-time localization, scene loading, annotation editing, and virtual–real rendering. MUCServer—as the bridge between MUCStudio and MUCView—presents collaborative and database services. To achieve this, we implemented the algorithms of local map establishment, global map registration, optimization, and network synchronization. The system provides AR services for diverse industrial processes via three collaborative ways—remote support, collaborative annotation, and editing. According to the system, applications for cutting machines were presented to improve efficiency and reduce costs, covering cutting head designs, production line sales, and cutting machine inspections. Finally, a user study was performed to prove the usage experience of the system.

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InspectAR: An Augmented Reality Inspection Framework for Industry

Cited by 17 publications

References 2 publications

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

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

Collaborative SLAM and AR-guided navigation for floor layout inspection

A Multi-User Collaborative AR System for Industrial Applications

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