Taban”:A Retro-Projected Social Robotic - Head for Human-Robot Interaction

2019 ◽  
Author(s):  
M. Mokhtari ◽  
A. Shariati ◽  
A. Meghdari
Keyword(s):  
Human Robot Interaction ◽  
Robot Interaction ◽  
Social Robotic

scholarly journals On the Integration of Adaptive and Interactive Robotic Smart Spaces

2015 ◽  
Vol 6 (1) ◽  
Author(s):  
Mauro Dragone ◽  
Joe Saunders ◽  
Kerstin Dautenhahn
Keyword(s):  
Intelligent Systems ◽  
Human Robot Interaction ◽  
Smart Spaces ◽  
Robotic Approach ◽  
Robot Interaction ◽  
Limited Degree ◽  
The One ◽  
New Generation ◽  
Social Robotic ◽  
Robotic Applications

AbstractEnabling robots to seamlessly operate as part of smart spaces is an important and extended challenge for robotics R&D and a key enabler for a range of advanced robotic applications, such as AmbientAssisted Living (AAL) and home automation. The integration of these technologies is currently being pursued from two largely distinct view-points: On the one hand, people-centred initiatives focus on improving the user’s acceptance by tackling human-robot interaction (HRI) issues, often adopting a social robotic approach, and by giving to the designer and - in a limited degree – to the final user(s), control on personalization and product customisation features. On the other hand, technologically-driven initiatives are building impersonal but intelligent systems that are able to pro-actively and autonomously adapt their operations to fit changing requirements and evolving users’ needs, but which largely ignore and do not leverage human-robot interaction and may thus lead to poor user experience and user acceptance. In order to inform the development of a new generation of smart robotic spaces, this paper analyses and compares different research strands with a view to proposing possible integrated solutions with both advanced HRI and online adaptation capabilities.

scholarly journals Multimodal social scenario perception model for initial human-robot interaction

2019 ◽  
Author(s):  
Diego Cardoso Alves ◽  
Paula Dornhofer Paro Costa
Keyword(s):  
Scene Perception ◽  
Human Robot Interaction ◽  
Social Model ◽  
Robot Interaction ◽  
Multimodal Sensing ◽  
Engagement Process ◽  
Perception Model ◽  
Audio Data ◽  
Social Robotic ◽  
Human Behavior Analysis

Human-robot interaction imposes many challenges and artificial intelligence researchers are demanded to improve scene perception, social navigation and engagement. Great attention is being dedicated to the development of computer vision and multimodal sensing approaches that are focused on the evolution of social robotic systems and the improvement of social model accuracy. Most recent works related to social robotics rely on the engagement process with a focus on maintaining a previously established conversation. This work brings up the study of initial human-robot interaction contexts, proposing a system that is able to analyze a social scenario through the detection and analysis of persons and surrounding features in a scene. RGB and depth frames, as well as audio data, were used in order to achieve better performance in indoor scene monitoring and human behavior analysis.

Workload in Human-Robot Interaction: A Review of Manipulations and Outcomes

2009 ◽  
Author(s):  
Matthew S. Prewett ◽  
Kristin N. Saboe ◽  
Ryan C. Johnson ◽  
Michael D. Coovert ◽  
Linda R. Elliott
Keyword(s):  
Human Robot Interaction ◽  
Robot Interaction

Biomimetic, sociable robots for human-robot interaction

2010 ◽  
Author(s):  
Eleanore Edson ◽  
Judith Lytle ◽  
Thomas McKenna
Keyword(s):  
Human Robot Interaction ◽  
Robot Interaction

The role and relationship of mindreading and social attunement in HRI – position statements of interdisciplinary researchers. Workshop HRI'20

2020 ◽  
Author(s):  
Agnieszka Wykowska ◽  
Jairo Pérez-Osorio ◽  
Stefan Kopp
Keyword(s):  
Mental States ◽  
Human Robot Interaction ◽  
Human Interaction ◽  
Artificial Agents ◽  
The Novel ◽  
Robot Interaction ◽  
Novel Coronavirus ◽  
Relationship Of ◽  
The Relationship

This booklet is a collection of the position statements accepted for the HRI’20 conference workshop “Social Cognition for HRI: Exploring the relationship between mindreading and social attunement in human-robot interaction” (Wykowska, Perez-Osorio & Kopp, 2020). Unfortunately, due to the rapid unfolding of the novel coronavirus at the beginning of the present year, the conference and consequently our workshop, were canceled. On the light of these events, we decided to put together the positions statements accepted for the workshop. The contributions collected in these pages highlight the role of attribution of mental states to artificial agents in human-robot interaction, and precisely the quality and presence of social attunement mechanisms that are known to make human interaction smooth, efficient, and robust. These papers also accentuate the importance of the multidisciplinary approach to advance the understanding of the factors and the consequences of social interactions with artificial agents.

Shall I trust you? From child human-robot interaction to trusting relationships

2019 ◽  
Author(s):  
Cinzia Di Dio ◽  
Federico Manzi ◽  
Giulia Peretti ◽  
Angelo Cangelosi ◽  
Paul L. Harris ◽  
...  
Keyword(s):  
Behavioral Pattern ◽  
Human Robot Interaction ◽  
School Age Children ◽  
Social Relevance ◽  
Robot Interaction ◽  
Cognitive Correlates ◽  
The Social ◽  
The Relationship

Studying trust within human-robot interaction is of great importance given the social relevance of robotic agents in a variety of contexts. We investigated the acquisition, loss and restoration of trust when preschool and school-age children played with either a human or a humanoid robot in-vivo. The relationship between trust and the quality of attachment relationships, Theory of Mind, and executive function skills was also investigated. No differences were found in children’s trust in the play-partner as a function of agency (human or robot). Nevertheless, 3-years-olds showed a trend toward trusting the human more than the robot, while 7-years-olds displayed the reverse behavioral pattern, thus highlighting the developing interplay between affective and cognitive correlates of trust.

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