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A survey of socially interactive robots

TLDR
The context for socially interactive robots is discussed, emphasizing the relationship to other research fields and the different forms of “social robots”, and a taxonomy of design methods and system components used to build socially interactive Robots is presented.
About
This article is published in Robotics and Autonomous Systems.The article was published on 2003-03-31 and is currently open access. It has received 2869 citations till now. The article focuses on the topics: Media Lab Europe's social robots & Human–robot interaction.

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Citations
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Journal ArticleDOI

A survey of robot learning from demonstration

TL;DR: A comprehensive survey of robot Learning from Demonstration (LfD), a technique that develops policies from example state to action mappings, which analyzes and categorizes the multiple ways in which examples are gathered, as well as the various techniques for policy derivation.
Journal ArticleDOI

Measurement instruments for the anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety of robots

TL;DR: A literature review has been performed on the measurements of five key concepts in HRI: anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety, distilled into five consistent questionnaires using semantic differential scales.
Book

Human-Robot Interaction: A Survey

TL;DR: The goal of this review is to present a unified treatment of HRI-related problems, to identify key themes, and discuss challenge problems that are likely to shape the field in the near future.

전자/제조업의 Collaboration 전략

조남욱
TL;DR: In this article, mental health issues often co-occur with other problems such as substance abuse, and they can take an enormous toll on individuals and impact a college or university in many ways.
Journal ArticleDOI

Multimodal human-computer interaction: A survey

TL;DR: This paper reviews the major approaches to multimodal human-computer interaction, giving an overview of the field from a computer vision perspective, and focuses on body, gesture, gaze, and affective interaction.
References
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Journal ArticleDOI

I show you how I like you - can you read it in my face? [robotics]

TL;DR: In this paper, a LEGO robot displays different emotional expressions in response to physical stimulation for the purpose of social interaction with humans, drawing inspiration from theories of human basic emotions, implemented several prototypical expressions in the robot's caricatured face and conducted experiments to assess the recognizability of these expressions.

Mental Models and Cooperation with Robotic Assistants

TL;DR: In this paper, the authors developed techniques for measuring the richness and content of people's mental models of a robot and found that participants had a comparatively rich mechanistic perception of the robot and perceived it to have some human traits, but not complex human attachment, foibles, or creativity.
Journal ArticleDOI

Grounding communication in autonomous robots: An experimental study

TL;DR: In this article, an imitative strategy is used to create a common perceptual context to learner and teacher agents, upon which the learner grounds its understanding of the teacher's words.
Book ChapterDOI

Affective Interaction between Humans and Robots

TL;DR: This paper presents a framework for addressing the role of emotive responses in communicative behavior between robots and humans, and demonstrates the robot's ability to engage naive human subjects in a compelling and expressive manner.
Book

Affective Interactions: Towards a New Generation of Computer Interfaces

TL;DR: A new field is emerging in computer science: affective computing as mentioned in this paper, i.e. computing that relates to, arises from, or deliberately influences emotions (e.g. emotions).
Frequently Asked Questions (12)
Q1. What contributions have the authors mentioned in the paper "A survey of socially interactive robots: concepts, design, and applications" ?

This report reviews “ socially interactive robots ”: robots for which social human-robot interaction is important. The authors begin by discussing the context for socially interactive robots, emphasizing the relationship to other research fields and the different forms of “ social robots ”. The authors then present a taxonomy of design methods and system components used to build socially interactive robots. Following this taxonomy, the authors survey the current state of the art, categorized by use and application area. Finally, the authors describe the impact of these these robots on humans and discuss open issues. An abbreviated version of this report, which does not contain the application survey, is available as [ T. Fong, I. Nourbakhsh, K. Dautenhahn, A survey of socially interactive robots, Robotics and Autonomous Systems 

Given that the authors expect social robots to play increasingly larger roles in daily life, there is a strong need for field studies to examine how people behave when robots are introduced into their activities. 

Others important advantages are:• Robots can provide a stimulating and motivating influence that make living conditions or particular treatments more pleasant and endurable, an effect that has particular potential for children or elderly people. 

The measures consist of: scales for rating anthropomorphic and mechanistic dimensions; measures of model richness or certainty; and measures of compliance with a robot’s requests. 

Following their ethic of task-based and contextbased design, Severinson-Eklundh et al. identified two critical communicative needs of a fetch-andcarry robot. 

The creation of compelling anthropomorphic robots is a massive engineering challenge; yet, in the case of both Sony and Honda it is clear that the single largest hurdle involved actuation. 

Through such empowerment, fear or shyness towards technology can be transformed dramatically into interest in exploring technology and even altering its course. 

Aoki et al. contend that studies of rat-like robots will lead to better understanding of human behavior, in the same manner that animal experimentation (especially on rats) does. 

They contend that directed instruction, whereby a human teaches a robot using a carefully engineered feedback and reward mechanism, is constraining and ultimately unable to scale. 

In part, the argument is that in order for a robot to interact with humans as humans do (through gaze, gesture, vocalization, etc.), it must be structurally and functionally similar to a human. 

There is reason to believe that if a robot had a compelling personality, people would be more willing to interact with it and to establish a relationship with it[27,116]. 

Although human-robot communication can occur in many different ways, the authors consider there to be three primary types of dialogue: low-level (pre-linguistic), non-verbal, and natural language.