Virtual Learning for Workers in Robot Deployed Construction Sites

Moon, Seungbin; Becerik-Gerber, Burçin; Soibelman, Lúcio

doi:10.1007/978-3-030-00220-6_107

Cited by 16 publications

(9 citation statements)

References 30 publications

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“…Accurate spatial updating is critical for a successful VE for nongaming purposes. Example applications include use of a VE for firefighter training aboard Navy ships (Tate, Sibert, & King, 1997), training of electrical plant maintenance (De Sousa, Filho, Nunes, & Lopes, 2010), virtual tourism (Go & Gretzel, 2010), and construction site safety training (Moon, Becerik-Gerber, & Soibelman, 2019). The current study investigated the influence of two common teleporting interfaces on spatial updating in VEs with and without piloting cues.…”

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confidence: 99%

Spatial cognitive implications of teleporting through virtual environments.

Cherep

Lim

Kelly

et al. 2020

Journal of Experimental Psychology: Applied

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Teleporting is a popular interface to allow virtual reality users to explore environments that are larger than the available walking space. When teleporting, the user positions a marker in the virtual environment and is instantly transported without any self-motion cues. Five experiments were designed to evaluate the spatial cognitive consequences of teleporting and to identify environmental cues that could mitigate those costs. Participants performed a triangle completion task by traversing two outbound path legs before pointing to the unmarked path origin. Locomotion was accomplished via walking or two common implementations of the teleporting interface distinguished by the concordance between movement of the body and movement through the virtual environment. In the partially concordant teleporting interface, participants teleported to translate (change position) but turned the body to rotate. In the discordant teleporting interface, participants teleported to translate and rotate. Across all five experiments, discordant teleporting produced larger errors than partially concordant teleporting which produced larger errors than walking, reflecting the importance of translational and rotational selfmotion cues. Furthermore, geometric boundaries (room walls or a fence) were necessary to mitigate the spatial cognitive costs associated with teleporting, and landmarks were helpful only in the context of a geometric boundary. Public Significance Statement: Movement through a virtual environment (VE) can be accomplished by walking, but physical space constraints require a navigation interface. One popular interface is teleporting, whereby the user points to a place in the VE and is instantly transported there. In this study, we reveal that teleporting can lead to spatial disorientation due to lack of self-motion cues. Boundaries in the VE, such as walls or a fence, reduce but do not eliminate the disorienting effect of teleporting.

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mentioning

confidence: 99%

Spatial cognitive implications of teleporting through virtual environments.

Cherep

Lim

Kelly

et al. 2020

Journal of Experimental Psychology: Applied

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“…This technique is used to configure the devices, which are connected over the Internet. Data collection and analysis from different means—feedback, production, enterprise, requests, etc.—improved the decision making process in smart manufacturing [ 17 , 18 ]. During these developments, manufacturers and customers provided feedback and their points of view related to the products, which helped the manufacturers improve product quality, design, etc.…”

Section: Related Workmentioning

confidence: 99%

Integration of Blockchain, IoT and Machine Learning for Multistage Quality Control and Enhancing Security in Smart Manufacturing

Shahbazi

Byun

2021

Sensors

110

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Smart manufacturing systems are growing based on the various requests for predicting the reliability and quality of equipment. Many machine learning techniques are being examined to that end. Another issue which considers an important part of industry is data security and management. To overcome the problems mentioned above, we applied the integrated methods of blockchain and machine learning to secure system transactions and handle a dataset to overcome the fake dataset. To manage and analyze the collected dataset, big data techniques were used. The blockchain system was implemented in the private Hyperledger Fabric platform. Similarly, the fault diagnosis prediction aspect was evaluated based on the hybrid prediction technique. The system’s quality control was evaluated based on non-linear machine learning techniques, which modeled that complex environment and found the true positive rate of the system’s quality control approach.

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“…The training spans from basic job skills to advanced interactions in robot deployed workplaces. The current learning opportunities in the construction industry are mostly conventional lecture-based classroom learning or hands on training, with the former being inadequate and the latter being costly (Moon et al, 2019).…”

Section: Trainingmentioning

confidence: 99%

“…Virtual learning environments (VLEs) can be an alternative learning platform for training in workers' interactions with AI/robots. However, research shows that around 53% use a PC monitor for visualization and a mouse and keyboard as the user interface which does not provide a realistic experience for the user (Moon et al, 2019). Only about 17% in this field use power walls for training, which provide an immersive environment with active glasses (Moon et al, 2019).…”

Section: Trainingmentioning

confidence: 99%

“…However, research shows that around 53% use a PC monitor for visualization and a mouse and keyboard as the user interface which does not provide a realistic experience for the user (Moon et al, 2019). Only about 17% in this field use power walls for training, which provide an immersive environment with active glasses (Moon et al, 2019). In addition to power walls, head mounted displays (e.g., oculus rift™) are also used with controllers.…”

Section: Trainingmentioning

confidence: 99%

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Human Factors Considerations for Teaming between Construction Workersand Voice-based Intelligent Virtual Agent (VIVA)

Movassagh

Roofigari‐Esfahan

Lee

et al. 2021

Proceedings of the Human Factors and Ergonomics Society Annual

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Construction sites experience low productivity due to particular characteristics such as unique designs in each project, sporadic arrival of projects, and complexity of the process. Another contributing factor to low productivity is poor communication among workers, supervisors, and a site’s centralized knowledge hub. Research shows that introducing advanced artificial intelligence (AI) technology in construction can tackle these problems. In this paper, we analyzed human factors considerations–user, task, environment, and technology and identified their characteristics and challenges to design an interactive AI system to facilitate communication between workers and other stakeholders. Based on the analysis, we propose a voice-based intelligent virtual agent (VIVA) as a multi-purpose AI system on construction sites with a further research agenda. We hope that this effort can guide the design of construction-specific AI systems and that this worker-AI teaming can improve overall work processes, enhance productivity, and promote safety in construction.

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Virtual Learning for Workers in Robot Deployed Construction Sites

Cited by 16 publications

References 30 publications

Spatial cognitive implications of teleporting through virtual environments.

Spatial cognitive implications of teleporting through virtual environments.

Integration of Blockchain, IoT and Machine Learning for Multistage Quality Control and Enhancing Security in Smart Manufacturing

Human Factors Considerations for Teaming between Construction Workersand Voice-based Intelligent Virtual Agent (VIVA)

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