With the pandemic preventing access to universities and consequently limiting in-person user studies, it is imperative to explore other mediums for conducting user studies for human-robot interaction. Virtual reality (VR) presents a novel and promising research platform that can potentially offer a creative and accessible environment for HRI studies. Despite access to VR being limited given its hardware requirements (e.g. need for headsets), web-based VR offers universal access to VR utilities through web browsers. In this paper, we present a participatory design pilot study, aimed at exploring the use of co-design of a robot using web-based VR. Results seem to show that web-based VR environments are engaging and accessible research platforms to gather environment and interaction data in HRI.
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Exploring Interaction Design Considerations for Trustworthy Language-Capable Robotic Wheelchairs in Virtual Reality
In previous work, researchers in Human-Robot Interaction (HRI) have demonstrated that user trust in robots depends on effective and transparent communication. This may be particularly true for robots used for transportation, due to user reliance on such robots for physical movement and safety. In this paper, we present the design of an experiment examining the importance of proactive communication by robotic wheelchairs, as compared to non-vehicular mobile robots, within a Virtual Reality (VR) environment. Furthermore, we describe the specific advantages – and limitations – of conducting this type of HRI experiment in VR.
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- Award ID(s):
- 1823245
- NSF-PAR ID:
- 10155103
- Date Published:
- Journal Name:
- International Workshop on Virtual, Augmented, and Mixed Reality for Human-Robot Interaction
- Volume:
- 3
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Effective interactions between humans and robots are vital to achieving shared tasks in collaborative processes. Robots can utilize diverse communication channels to interact with humans, such as hearing, speech, sight, touch, and learning. Our focus, amidst the various means of interactions between humans and robots, is on three emerging frontiers that significantly impact the future directions of human–robot interaction (HRI): (i) human–robot collaboration inspired by human–human collaboration, (ii) brain-computer interfaces, and (iii) emotional intelligent perception. First, we explore advanced techniques for human–robot collaboration, covering a range of methods from compliance and performance-based approaches to synergistic and learning-based strategies, including learning from demonstration, active learning, and learning from complex tasks. Then, we examine innovative uses of brain-computer interfaces for enhancing HRI, with a focus on applications in rehabilitation, communication, brain state and emotion recognition. Finally, we investigate the emotional intelligence in robotics, focusing on translating human emotions to robots via facial expressions, body gestures, and eye-tracking for fluid, natural interactions. Recent developments in these emerging frontiers and their impact on HRI were detailed and discussed. We highlight contemporary trends and emerging advancements in the field. Ultimately, this paper underscores the necessity of a multimodal approach in developing systems capable of adaptive behavior and effective interaction between humans and robots, thus offering a thorough understanding of the diverse modalities essential for maximizing the potential of HRI.
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Extended reality (XR) technologies, such as virtual reality (VR) and augmented reality (AR), provide users, their avatars, and embodied agents a shared platform to collaborate in a spatial context. Although traditional face-to-face communication is limited by users’ proximity, meaning that another human’s non-verbal embodied cues become more difficult to perceive the farther one is away from that person, researchers and practitioners have started to look into ways to accentuate or amplify such embodied cues and signals to counteract the effects of distance with XR technologies. In this article, we describe and evaluate the Big Head technique, in which a human’s head in VR/AR is scaled up relative to their distance from the observer as a mechanism for enhancing the visibility of non-verbal facial cues, such as facial expressions or eye gaze. To better understand and explore this technique, we present two complimentary human-subject experiments in this article. In our first experiment, we conducted a VR study with a head-mounted display to understand the impact of increased or decreased head scales on participants’ ability to perceive facial expressions as well as their sense of comfort and feeling of “uncannniness” over distances of up to 10 m. We explored two different scaling methods and compared perceptual thresholds and user preferences. Our second experiment was performed in an outdoor AR environment with an optical see-through head-mounted display. Participants were asked to estimate facial expressions and eye gaze, and identify a virtual human over large distances of 30, 60, and 90 m. In both experiments, our results show significant differences in minimum, maximum, and ideal head scales for different distances and tasks related to perceiving faces, facial expressions, and eye gaze, and we also found that participants were more comfortable with slightly bigger heads at larger distances. We discuss our findings with respect to the technologies used, and we discuss implications and guidelines for practical applications that aim to leverage XR-enhanced facial cues.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.31219/osf.io/72qgt
