Exploring Head Mounted Display based Augmented Reality for Factory Workers

Väyrynen, Jani; Suoheimo, Mari; Colley, Ashley; Häkkilä, Jonna

doi:10.1145/3282894.3289745

Cited by 9 publications

(7 citation statements)

References 20 publications

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“…Furthermore, 10 papers concerning head or speech input discussed how systems could adapt for hands-free interaction approaches. This predominantly included applications for healthcare or maintenance [8,45,68,74,86], where users are generally required to operate their hands to complete real-world tasks, and for text entry, where it may be inconvenient to use an external controller, or look down to type on a smartphone [48,95].…”

Section: Input Methodsmentioning

confidence: 99%

“…18 papers were considered only relevant to a specific implementation, whereas 12 explored fundamental findings and went on to apply them to a final application. Notable areas of contribution surround selection [12,26,30], object manipulation [20,63,90], text entry [48,95], game interaction [14,82], character control and animation [3,96], human-human [86] and human-robot collaboration [31,43], map exploration [76], UI (user interface) and menu-based interaction [8,67], Medical/Healthcare [68,74], interactive learning [9,57] and AR assistants [51,99]. Some studies could be classified into more than one of these categories, such as the work of Sadri et al [74], which focuses on anatomic model manipulation for medical applications.…”

Section: Type Of Studymentioning

confidence: 99%

“…Studies conducted 'in the wild' were primarily related to specific use cases (i.e. a cultural heritage site [15], care home [68] or in an industrial environment [69,86]), with Alallah et al [1] exploring fundamental interaction in public spaces. Participants were again asked to remain static for most studies.…”

Section: Study Typementioning

confidence: 99%

“…Speech has also been found to be less natural for applications with a single user [67]. However, as speech is inherently employed for humanto-human communication, voice-based input is arguably more appropriate for collaborative environments, such as for remote assistance applications, as verbal communication can be applied more intuitively [86]. Employing speech interaction has also been found to increase memory retention and learning for educational applications [18].…”

Section: General Findingsmentioning

confidence: 99%

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A Review of Interaction Techniques for Immersive Environments

Spittle

Frutos-Pascual

Creed

et al. 2023

IEEE Trans. Visual. Comput. Graphics

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The recent proliferation of immersive technology has led to the rapid adoption of consumer-ready hardware for Augmented Reality (AR) and Virtual Reality (VR). While this increase has resulted in a variety of platforms that can offer a richer interactive experience, the advances in technology bring more variability in display types, interaction sensors and use cases. This provides a spectrum of device-specific interaction possibilities, with each offering a tailor-made solution for delivering immersive experiences to users, but often with an inherent lack of standardisation across devices and applications. To address this, a systematic review and an evaluation of explicit, task-based interaction methods in immersive environments are presented in this paper. A corpus of papers published between 2013 and 2020 is reviewed to thoroughly explore state-of-the-art user studies, which investigate input methods and their implementation for immersive interaction tasks (pointing, selection, translation, rotation, scale, viewport, menu-based and abstract). Focus is given to how input methods have been applied within the spectrum of immersive technology (AR, VR, XR). This is achieved by categorising findings based on display type, input method, study type, use case and task. Results illustrate key trends surrounding the benefits and limitations of each interaction technique and highlight the gaps in current research. The review provides a foundation for understanding the current and future directions for interaction studies in immersive environments, which, at this pivotal point in XR technology adoption, provides routes forward for achieving more valuable, intuitive and natural interactive experiences.

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Section: Input Methodsmentioning

confidence: 99%

Section: Type Of Studymentioning

confidence: 99%

Section: Study Typementioning

confidence: 99%

Section: General Findingsmentioning

confidence: 99%

See 2 more Smart Citations

A Review of Interaction Techniques for Immersive Environments

Spittle

Frutos-Pascual

Creed

et al. 2023

IEEE Trans. Visual. Comput. Graphics

View full text Add to dashboard Cite

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“…Furht, 2011) with some researchers referring to this activity as "industrial AR" (Fite-Georgel, 2011;Quandt & Freitag, 2021) or "iAR" (Gattullo et al, 2020). However, broader operational deployment has been constrained (Quandt & Freitag, 2021;Väyrynen et al, 2018;Wang et al, 2021) and industry use of AR beyond the prototype stage is generally low (Zigart & Schlund, 2020) (Park et al, 2021) and aims to address these requirements (e.g., Evans et al, 2017).…”

Section: The Current State Of Industrial Ar Uptakementioning

confidence: 99%

Visual inspection with augmented reality head‐mounted display: An Australian usability case study

Howard

Jang

O’Keeffe

et al. 2023

Hum Ftrs & Erg Mfg Svc

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Augmented reality (AR) is an Industry 4.0 technology. For more than a decade, advancements in AR technology and their applications have been expected to revolutionise the manufacturing industry and deliver quality and productivity gains. However, due to factors such as equipment costs, skills shortages and technological limitations of AR devices, operational deployment beyond prototypes has been constrained. Real‐world, usability studies can explore barriers to implementation and improve system design. This paper details a mixed method usability case study of an AR head‐mounted display (HMD) to perform a short, simple visual inspection task. Twenty‐two participants from South Australian manufacturing businesses inspected a pump and pipe skid while working at height. Overall, workload demands for the task were considered acceptable and just below the “low” workload threshold (NASA Task Load Index, mean = 29.3) and the system usability was rated “average” (system usability scale, mean = 68.5). The results suggest the task did not place too high a burden on users and was an appropriate initial exposure to AR HMDs, but further refinement to the interface would be desirable before implementation to minimise frustration and promote learning. Users were enthusiastic and open‐minded about the AR HMD although results indicate that even with recent advancements in AR HMD technology, interactions between the task, technology and environment continue to cause human and technical challenges—some of which are relatively straightforward to address but others are dependent on larger‐scale efforts.

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