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Benjamin A. Blumer

dblp:142/3021 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2014
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Human-computer interaction and ubiquitous computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Human-robot interaction · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-robot interaction › nonverbal communication
gaze cue
0.212014
Meet me where i'm gazing: how shared attention gaze affects human-robot handover timing · HRI 2014
Human-robot interaction
nonverbal communication
0.212014
Meet me where i'm gazing: how shared attention gaze affects human-robot handover timing · HRI 2014
Human-robot interaction › physical human-robot interaction
object handover
0.212014
Meet me where i'm gazing: how shared attention gaze affects human-robot handover timing · HRI 2014
Human-robot interaction › nonverbal communication
joint attention
0.112014
Meet me where i'm gazing: how shared attention gaze affects human-robot handover timing · HRI 2014

Methods — techniques the papers use, named apart from their topics

user study · 0.2gaze behavior implementation · 0.2
YearPublicationVenuePosition
2014 Meet me where i'm gazing: how shared attention gaze affects human-robot handover timing
abstract
In this paper we provide empirical evidence that using humanlike gaze cues during human-robot handovers can improve the timing and perceived quality of the handover event. Handovers serve as the foundation of many human-robot tasks. Fluent, legible handover interactions require appropriate nonverbal cues to signal handover intent, location and timing. Inspired by observations of human-human handovers, we implemented gaze behaviors on a PR2 humanoid robot. The robot handed over water bottles to a total of 102 naïve subjects while varying its gaze behaviour: no gaze, gaze designed to elicit shared attention at the handover location, and the shared attention gaze complemented with a turn-taking cue. We compared subject perception of and reaction time to the robot-initiated handovers across the three gaze conditions. Results indicate that subjects reach for the offered object significantly earlier when a robot provides a shared attention gaze cue during a handover. We also observed a statistical trend of subjects preferring handovers with turn-taking gaze cues over the other conditions. Our work demonstrates that gaze can play a key role in improving user experience of human-robot handovers, and help make handovers fast and fluent.
AJung Moon, Daniel Troniak, Brian T. Gleeson, Matthew K. X. J. Pan, Minhua Zheng, Benjamin A. Blumer, Karon E. MacLean, Elizabeth A. Croft
HRI6