Toward a Context-Aware Human–Robot Interaction Framework Based on Cognitive Development

2019 ◽  
Vol 49 (1) ◽  
pp. 227-237 ◽  
Author(s):  
Joao Quintas ◽  
Goncalo S. Martins ◽  
Luis Santos ◽  
Paulo Menezes ◽  
Jorge Dias
Keyword(s):  
Cognitive Development ◽  
Human Robot Interaction ◽  
Context Aware ◽  
Robot Interaction

Learning Hidden Human Context in 3D Office Scenes by Mapping Affordances Through Virtual Humans

2015 ◽  
Vol 03 (04) ◽  
pp. 299-310
Author(s):  
Lasitha Piyathilaka ◽  
Sarath Kodagoda
Keyword(s):  
Point Cloud ◽  
Search Strategy ◽  
Human Robot Interaction ◽  
Context Aware ◽  
Point Cloud Data ◽  
Active Object ◽  
Robot Interaction ◽  
Cloud Data ◽  
Planning Strategy ◽  
Object Search

Ability to learn human context in an environment could be one of the most desired fundamental abilities that a robot should have when sharing a workspace with human co-workers. Arguably, a robot with appropriate human context awareness could lead to a better human–robot interaction. In this paper, we address the problem of learning human context in an office environment by only using 3D point cloud data. Our approach is based on the concept of affordance-map, which involves mapping latent human actions in a given environment by looking at geometric features of the environment. This enables us to learn the human context in the environment without observing real human behaviors which themselves are a nontrivial task to detect. Once learned, affordance-map allows us to assign an affordance cost value for each grid location of the map. These cost maps are later used to develop an active object search strategy and to develop a context-aware global path planning strategy.

scholarly journals An Evaluation of Human Conversational Preferences in Social Human-Robot Interaction

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Chapa Sirithunge ◽  
A. G. Buddhika P. Jayasekara ◽  
D. P. Chandima
Keyword(s):  
Human Study ◽  
Social Robot ◽  
Human Robot Interaction ◽  
Context Aware ◽  
Careful Evaluation ◽  
Robot Interaction ◽  
Wizard Of Oz ◽  
Social Encounter

To generate context-aware behaviors in robots, robots are required to have a careful evaluation of its encounters with humans. Unwrapping emotional hints in observable cues in an encounter will improve a robot’s etiquettes in a social encounter. This article presents an extended human study conducted to examine how several factors in an encounter influence a person’s preferences upon an interaction at a particular moment. We analyzed the nature of conversation preferred by a user considering the type of conversation a robot could have with its user, having the interaction initiated by the robot itself. We took an effort to explore how such preferences differ as the factors present in the surrounding alter. A social robot equipped with the capability to initiate a conversation is deployed to conduct the study by means of a wizard-of-oz (WoZ) experiment. During this study, conversational preferences of users could vary from “no interaction at all” to a “long conversation.” We changed three factors in an encounter which can be different from each other in each circumstance: the audience or outsiders in the environment, user’s task, and the domestic area in which the interaction takes place. Conversational preferences of users within the abovementioned conditions were analyzed in a later stage, and critical observations are highlighted. Finally, implications that could be helpful in shaping future social human-robot encounters were derived from the analysis of the results.

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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