A Study of Preference and Comfort for Users Immersed in a Telepresence Robot
March 05, 2022 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Adhi Widagdo, Markku Suomalainen, Basak Sakcak, Katherine J. Mimnaugh, Juho Kalliokoski, Alexis P. Chambers, Timo Ojala, Steven M. LaValle
arXiv ID
2203.02699
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.MM,
cs.RO
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
In this paper, we show that unwinding the rotations of a user immersed in a telepresence robot is preferred and may increase the feeling of presence or "being there". By immersive telepresence, we mean a scenario where a user wearing a head-mounted display embodies a mobile robot equipped with a 360Β° camera in another location, such that the user can move the robot and communicate with people around it. By unwinding the rotations, the user never perceives rotational motion through the head-mounted display while staying stationary, avoiding sensory mismatch which causes a major part of VR sickness. We performed a user study (N=32) on a Dolly mobile robot platform, mimicking an earlier similar study done in simulation. Unlike the simulated study, in this study there is no significant difference in the VR sickness suffered by the participants, or the condition they find more comfortable (unwinding or automatic rotations). However, participants still prefer the unwinding condition, and they judge it to render a stronger feeling of presence, a major piece in natural communication. We show that participants aboard a real telepresence robot perceive distances similarly suitable as in simulation, presenting further evidence on the applicability of VR as a research platform for robotics and human-robot interaction.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted