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Aziez Sardar

dblp:12/10496 · DBLP profile ↗
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2ranked-venue papers
1as first author
1since 2021 · last 2021
—ORCID · none

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

Human-computer interaction and ubiquitous computing · 2 · 1 first-author · 1 since 2021Artificial intelligence and machine learning · 1 · 1 first-author

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
Collaborative and social computing · 77% Human-robot interaction · 23%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Collaborative and social computing › collaborative virtual environments › social virtual reality
personal space
0.112012
Don't stand so close to me: users' attitudinal and behavioral responses to personal space invasion by robots · HRI 2012
Human-robot interaction › multi-robot systems › spatial formation
proxemics
0.012012
Don't stand so close to me: users' attitudinal and behavioral responses to personal space invasion by robots · HRI 2012
YearPublicationVenuePosition
2021 Making Appearances: How Robots Should Approach People
abstract
To prepare for a future in which robots are more commonplace, it is important to know what robot behaviors people find socially normative. Previous work suggests that for robots to be accepted by people, the robot should adhere to the prevalent social norms, such as those related to approaching people. However, we do not expect that socially normative approach behaviors for robots can be translated on a one-on-one basis from people to robots, because currently robots have unique and different features to humans, including (but not limited to) wheels, sounds, and shapes. The two studies presented in this article go beyond the state-of-the-art and focus on socially normative approach behaviors for robots. In the first study, we compared people’s responses to violations of personal space done by robots compared to people. In the second study, we explored what features (sound, size, speed) of a robot approaching people have an effect on acceptance. Findings indicate that people are more lenient toward violations of a social norm by a robot as compared to a person. Also, we found that robots can use their unique features to mitigate the negative effects of norm violations by communicating intent.
Michiel Joosse, Manja Lohse, Niels van Berkel, Aziez Sardar, Vanessa Evers
ACM Trans. Hum. Robot Interact.4
2012 Don't stand so close to me: users' attitudinal and behavioral responses to personal space invasion by robots
abstract
When in a human environment, one might expect that a social robot would act according to the social norms people expect of each other. When someone does not adhere to a prevalent social norm, people usually feel threatened and disturbed. Thus, insight is needed into what is perceived as socially normative behavior for robots. We conducted an experiment in which an agent approached a participant in order to determine the effect of personal space invasion. We manipulated the agent-type (human/robot) and the approach speed (slow/fast) of the agent towards the participant. Unexpectedly, our results show that the participants displayed more compensatory behavior in the robot condition than in the human condition. We consider this response toward personal space invasion as indication that people react in a similar way to robots as they do to humans, however with more intensity.
Aziez Sardar, Michiel Joosse, Astrid Weiss, Vanessa Evers
HRI1