5 research outputs found
The Six Hug Commandments: Design and Evaluation of a Human-Sized Hugging Robot with Visual and Haptic Perception
Receiving a hug is one of the best ways to feel socially supported, and the
lack of social touch can have severe negative effects on an individual's
well-being. Based on previous research both within and outside of HRI, we
propose six tenets ("commandments") of natural and enjoyable robotic hugging: a
hugging robot should be soft, be warm, be human sized, visually perceive its
user, adjust its embrace to the user's size and position, and reliably release
when the user wants to end the hug. Prior work validated the first two tenets,
and the final four are new. We followed all six tenets to create a new robotic
platform, HuggieBot 2.0, that has a soft, warm, inflated body (HuggieChest) and
uses visual and haptic sensing to deliver closed-loop hugging. We first
verified the outward appeal of this platform in comparison to the previous
PR2-based HuggieBot 1.0 via an online video-watching study involving 117 users.
We then conducted an in-person experiment in which 32 users each exchanged
eight hugs with HuggieBot 2.0, experiencing all combinations of visual hug
initiation, haptic sizing, and haptic releasing. The results show that adding
haptic reactivity definitively improves user perception a hugging robot,
largely verifying our four new tenets and illuminating several interesting
opportunities for further improvement.Comment: 9 pages, 6 Figures, 2 Tables, ACM/IEEE Human-Robot Interaction (HRI)
Conference 202
Sharing Stress With a Robot: What Would a Robot Say?
With the prevalence of mental health problems today, designing human-robot interaction for mental health intervention is not only possible, but critical. The current experiment examined how three types of robot disclosure (emotional, technical, and by-proxy) affect robot perception and human disclosure behavior during a stress-sharing activity. Emotional robot disclosure resulted in the lowest robot perceived safety. Post-hoc analysis revealed that increased perceived stress predicted reduced human disclosure, user satisfaction, robot likability, and future robot use. Negative attitudes toward robots also predicted reduced intention for future robot use. This work informs on the possible design of robot disclosure, as well as how individual attributes, such as perceived stress, can impact human robot interaction in a mental health context
Human-Machine Communication: Complete Volume. Volume 1
This is the complete volume of HMC Volume 1