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Conference

International Conference on Social Robotics 

About: International Conference on Social Robotics is an academic conference. The conference publishes majorly in the area(s): Social robot & Robot. Over the lifetime, 767 publications have been published by the conference receiving 8083 citations.

Papers published on a yearly basis

Papers
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Book ChapterDOI
29 Oct 2012
TL;DR: This review provides a comprehensive understanding of anthropomorphism in robotics, collects and reports relevant references, and gives an outlook on anthropomorphic human-robot interaction.
Abstract: In this literature review we explain anthropomorphism and its role in the design of socially interactive robots and human-robot interaction. We illustrate the social phenomenon of anthropomorphism which describes people's tendency to attribute lifelike qualities to objects and other non lifelike artifacts. We present theoretical backgrounds from social sciences, and integrate related work from robotics research, including results from experiments with social robots. We present different approaches for anthropomorphic and humanlike form in a robot's design related to its physical shape, its behavior, and its interaction with humans. This review provides a comprehensive understanding of anthropomorphism in robotics, collects and reports relevant references, and gives an outlook on anthropomorphic human-robot interaction.

246 citations

Book ChapterDOI
27 Oct 2013
TL;DR: This work provides the first demonstration of the ability to train multiple behaviors by such feedback without algorithmic modifications and of a robot learning from free-form human-generated feedback without any further guidance or evaluative feedback.
Abstract: We present a case study of applying a framework for learning from numeric human feedback–tamer–to a physically embodied robot. In doing so, we also provide the first demonstration of the ability to train multiple behaviors by such feedback without algorithmic modifications and of a robot learning from free-form human-generated feedback without any further guidance or evaluative feedback. We describe transparency challenges specific to a physically embodied robot learning from human feedback and adjustments that address these challenges.

135 citations

Book ChapterDOI
27 Oct 2013
TL;DR: In this article, a view on the opportunities offered by letting robots interact with children rather than with adults and having the interaction in real-world circumstances rather than lab settings is presented.
Abstract: Child-Robot Interaction (cHRI) is a promising point of entry into the rich challenge that social HRI is Starting from three years of experiences gained in a cHRI research project, this paper offers a view on the opportunities offered by letting robots interact with children rather than with adults and having the interaction in real-world circumstances rather than lab settings It identifies the main challenges which face the field of cHRI: the technical challenges, while tremendous, might be overcome by moving away from the classical perspective of seeing social cognition as residing inside an agent, to seeing social cognition as a continuous and self-correcting interaction between two agents

98 citations

Book ChapterDOI
24 Nov 2011
TL;DR: Results indicated that only gazing independently led to increased persuasiveness when the robot combined it with (the persuasive strategy of) gazing, and without gazing, using persuasive gestures diminished robot persuadeasiveness.
Abstract: Social agency theory suggests that when an (artificial) agent combines persuasive strategies, its persuasive power increases. Therefore, we investigated whether a robot that uses two persuasive strategies is more persuasive than a robot that uses only one. Because in human face-to-face persuasion two crucial persuasive strategies are gazing and gestures, the current research investigated the combined and individual contribution of gestures and gazing on the persuasiveness of a storytelling robot. A robot told a persuasive story about the aversive consequences of lying to 48 participants. The robot used persuasive gestures (or not) and gazing (or not) to accompany this persuasive story. We assessed persuasiveness by asking participants to evaluate the lying individual in the story told by the robot. Results indicated that only gazing independently led to increased persuasiveness. Using persuasive gestures only led to increased persuasiveness when the robot combined it with (the persuasive strategy of) gazing. Without gazing, using persuasive gestures diminished robot persuasiveness. The implications of the current findings for theory and design of persuasive robots are discussed.

91 citations

Book ChapterDOI
26 Oct 2015
TL;DR: The effects of a robot apologizing for its mistake, promising to do better in the future, and providing additional reasons to trust it in a simulated office evacuation conducted in a virtual environment are evaluated.
Abstract: Even the best robots will eventually make a mistake while performing their tasks. In our past experiments, we have found that even one mistake can cause a large loss in trust by human users. In this paper, we evaluate the effects of a robot apologizing for its mistake, promising to do better in the future, and providing additional reasons to trust it in a simulated office evacuation conducted in a virtual environment. In tests with 319 participants, we find that each of these techniques can be successful at repairing trust if they are used when the robot asks the human to trust it again, but are not successful when used immediately after the mistake. The implications of these results are discussed.

87 citations

Performance
Metrics
No. of papers from the Conference in previous years
YearPapers
202179
202057
201972
201861
201775
201699