Evaluation of Human Behavior Difference with Restricted Field of View in Real and VR Environments

Mizuchi, Yoshiaki; Inamura, Tetsunari

doi:10.1109/roman.2018.8525840

Cited by 7 publications

(7 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Five citations are from 2018 (Janis and Alias 2018;Marszalek and Volz 2018;Mizuchi and Inamura 2018;Ottogalli et al 2018;Shu et al 2018), eight citations are from 2019 (Chang et al 2019;Gao et al 2019bGao et al , 2019aMoon et al 2019;Ojstersek et al 2019;Randon and Cecconello 2019;Shu and Sziebig 2019;Yan et al 2019) and five citations are from 2020 (Anik et al 2020;Malik et al 2020;Metzner, Utsch, et al 2020;Peruzzini et al 2020).…”

Section: Researchgatementioning

confidence: 99%

“…However, there is one paper that has been uploaded twice using the format "code" and the number of real citations is 18. Of these, four are journal articles (Anik et al 2020;Malik et al 2020;Peruzzini et al 2020;Randon and Cecconello 2019), twelve are conference papers (H.-P. Chang et al 2019;Gao et al 2019b;Janis and Alias 2018;Metzner, Krieg, et al 2020;Mizuchi and Inamura 2018;Moon et al 2019;Ojstersek et al 2019;Ottogalli et al 2018;Shu et al 2018;Shu and Sziebig 2019;Yan et al 2019) and two are preprints (Gao et al 2019a;Marszalek and Volz 2018). One of the journal articles is in Portuguese (Randon and Cecconello 2019).…”

Section: Researchgatementioning

confidence: 99%

“…Semantic Scholar lists 19 citations for the paper. Four are journal articles (Anik et al 2020;Malik et al 2020;Oliveira Valério et al 2020;Peruzzini et al 2020), thirteen are conference papers (H.-P. Chang et al 2019;Gao et al 2019b;Janis and Alias 2018;Metzner, Krieg, et al 2020;Metzner, Utsch, et al 2020;Mizuchi and Inamura 2018;Moon et al 2019;Ojstersek et al 2019;Ottogalli et al 2018;Shu et al 2018;Shu and Sziebig 2019;Yan et al 2019) and one is a preprint (Gao et al 2019a). One citation is wrongly directed to the whole conference proceedings containing the conference paper "Intuitive, VR-and Gesturebased Physical Interaction with Virtual Commissioning Simulation Models" (Metzner, Krieg, et al 2020).…”

Section: Semantic Scholarmentioning

confidence: 99%

See 2 more Smart Citations

Citation review of Human-Machine Collaboration in Virtual Reality for Adaptive Production Engineering by de Giorgio et al.

Giorgio¹,

Onori²

2020

Preprint

View full text Add to dashboard Cite

This article argues that despite a citation review is a rarely used research tool, this can be very useful to assess the impact of new research topics, both from the future research direction and the bibliometric perspectives. An explorative study is presented around the research area marked as Industry 4.0 with the conference paper mentioned in the title of this citation review. Even though the given reference paper is relatively recent, there are already twenty-seven citations listed among three different scholar databases. These are Google Scholar, ResearchGate and Semantic Scholar. In light of this, the article provides a bibliometric confirmation and analysis for the progression of the line of research adopted by de Giorgio et al. in the exploration of non-traditional methods using virtual reality technology and human-robot collaboration for adaptive applications in Industry 4.0. Furthermore, it represents a model for the authors’ self-development and an example of an unconventional approach to scientific work that may help improve related bibliometric research and scholar database strategies to index new articles and topics in the future.

show abstract

Section: Researchgatementioning

confidence: 99%

Section: Researchgatementioning

confidence: 99%

Section: Semantic Scholarmentioning

confidence: 99%

See 1 more Smart Citation

Citation review of Human-Machine Collaboration in Virtual Reality for Adaptive Production Engineering by de Giorgio et al.

Giorgio¹,

Onori²

2020

Preprint

View full text Add to dashboard Cite

show abstract

“…In a study by Shi et al (2019) examining fall risk behaviors, slight movement mismatches in the IVE when participants rotate their heads can affect their sense of presence (i.e., being there in the simulated world) (Figure 12). IVEs and scenarios should be designed to avoid large changes in participants' head direction, for example, putting participants in a narrow space (Mizuchi and Inamura, 2018).…”

Section: Changes In Participants' Head Directionsmentioning

confidence: 99%

Designing Immersive Virtual Environments for Human Behavior Research

Neo

Won

Shepley

2021

Front. Virtual Real.

View full text Add to dashboard Cite

What are strategies for the design of immersive virtual environments (IVEs) to understand environments’ influence on behaviors? To answer this question, we conducted a systematic review to assess peer-reviewed publications and conference proceedings on experimental and proof-of-concept studies that described the design, manipulation, and setup of the IVEs to examine behaviors influenced by the environment. Eighteen articles met the inclusion criteria. Our review identified key categories and proposed strategies in the following areas for consideration when deciding on the level of detail that should be included when prototyping IVEs for human behavior research: 1) the appropriate level of detail (primarily visual) in the environment: important commonly found environmental accessories, realistic textures, computational costs associated with increased details, and minimizing unnecessary details, 2) context: contextual element, cues, and animation social interactions, 3) social cues: including computer-controlled agent-avatars when necessary and animating social interactions, 4) self-avatars, navigation concerns, and changes in participants’ head directions, and 5) nonvisual sensory information: haptic feedback, audio, and olfactory cues.

show abstract

“…Because human perception differs in many aspects between actual reality and VR, we cannot simply replace the experimental environment with VR (Wijnen et al, 2020). Therefore, it is necessary to consider several conditions, such as differences in distance perception (Li et al, 2019), gaze control (Duchowski et al, 2014;Sidenmark and Gellersen, 2019), and visual perception owing to a narrow field of view (Willemsen et al, 2009;Mizuchi and Inamura, 2018).…”

Section: Provision Of a Uniform Experimental Condition For Participantsmentioning

confidence: 99%

SIGVerse: A Cloud-Based VR Platform for Research on Multimodal Human-Robot Interaction

Inamura

Mizuchi

2021

Front. Robot. AI

Self Cite

View full text Add to dashboard Cite

Research on Human-Robot Interaction (HRI) requires the substantial consideration of an experimental design, as well as a significant amount of time to practice the subject experiment. Recent technology in virtual reality (VR) can potentially address these time and effort challenges. The significant advantages of VR systems for HRI are: 1) cost reduction, as experimental facilities are not required in a real environment; 2) provision of the same environmental and embodied interaction conditions to test subjects; 3) visualization of arbitrary information and situations that cannot occur in reality, such as playback of past experiences, and 4) ease of access to an immersive and natural interface for robot/avatar teleoperations. Although VR tools with their features have been applied and developed in previous HRI research, all-encompassing tools or frameworks remain unavailable. In particular, the benefits of integration with cloud computing have not been comprehensively considered. Hence, the purpose of this study is to propose a research platform that can comprehensively provide the elements required for HRI research by integrating VR and cloud technologies. To realize a flexible and reusable system, we developed a real-time bridging mechanism between the robot operating system (ROS) and Unity. To confirm the feasibility of the system in a practical HRI scenario, we applied the proposed system to three case studies, including a robot competition named RoboCup@Home. via these case studies, we validated the system’s usefulness and its potential for the development and evaluation of social intelligence via multimodal HRI.

show abstract

Evaluation of Human Behavior Difference with Restricted Field of View in Real and VR Environments

Cited by 7 publications

References 20 publications

Citation review of Human-Machine Collaboration in Virtual Reality for Adaptive Production Engineering by de Giorgio et al.

Citation review of Human-Machine Collaboration in Virtual Reality for Adaptive Production Engineering by de Giorgio et al.

Designing Immersive Virtual Environments for Human Behavior Research

SIGVerse: A Cloud-Based VR Platform for Research on Multimodal Human-Robot Interaction

Contact Info

Product

Resources

About