Augmented Reality (AR) or Mixed Reality (MR) enables innovative interactions by overlaying virtual imagery over the physical world. For roboticists, this creates new opportunities to apply proven non-verbal interaction patterns, like gesture, to physically-limited robots. However, a wealth of HRI research has demonstrated that there are real benefits to physical embodiment (compared, e.g., to virtual robots displayed on screens). This suggests that AR augmentation of virtual robot parts could lead to similar challenges. In this work, we present the design of an experiment to objectively and subjectively compare the use of AR and physical arms for deictic gesture, in AR and physical task environments. Our future results will inform robot designers choosing between the use of physical and virtual arms, and provide new nuanced understanding of the use of mixed-reality technologies in HRI contexts. Index T
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RoboCare Design Workshop: Understanding, Translating, Operationalizing, and Scaling Up Design Knowledge Regarding Robotic Systems for Care Assistance
Robots and other autonomous agents are well-positioned in the research discourse to support the care of people with challenges such as physical and/or cognitive disabilities. However, designing these robots can be complex as it involves considering a wide range of factors (e.g., individual needs, physical environment, technology capabilities, digital literacy), stakeholders (e.g., care recipients, formal and informal caregivers, technology developers), and contexts (e.g., hospitals, nursing homes, outpatient care facilities, private homes). The challenges are in gaining design insights for this unique use case and translating this knowledge into actionable, generalizable guidelines for other designers. This one-day workshop seeks to bring together researchers with diverse expertise and experience across academia, healthcare, and industry, spanning perspectives from multiple disciplines, including design, robotics, and human-computer interaction, with the primary goal being a consensus on best practices for generating and operationalizing design knowledge for robotic systems for care settings.
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- Award ID(s):
- 1925043
- PAR ID:
- 10536758
- Publisher / Repository:
- ACM
- Date Published:
- ISBN:
- 9798400706325
- Page Range / eLocation ID:
- 421 to 423
- Format(s):
- Medium: X
- Location:
- IT University of Copenhagen Denmark
- Sponsoring Org:
- National Science Foundation
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