A Developmental Approach to the Study of Affective Bonds for Human-Robot Interaction

Robotics agents are meant to play an increasingly larger role in our everyday lives. To be successfully integrated in our environment, robots will need to develop and display adaptive, robust, and socially suitable behaviours. To tackle these issues, the robotics research community has invested a considerable amount of efforts in modelling robotic architectures inspired by research on living systems, from ethology to developmental psychology. Following a similar approach, this thesis presents the research results of the modelling and experimental testing of robotic architectures based on affective and attachment bonds between young infants and their primary caregiver. I follow a bottom-up approach to the modelling of such bonds, examining how they can promote the situated development of an autonomous robot. Specifically, the models used and the results from the experiments carried out in laboratory settings and with naive users demonstrate the impact such affective bonds have on the learning outcomes of an autonomous robot and on the perception and behaviour of humans. This research leads to the emphasis on the importance of the interplay between the dynamics of the regulatory behaviours performed by a robot and the responsiveness of the human partner. The coupling of such signals and behaviours in an attachment-like dyad determines the nature of the outcomes for the robot, in terms of learning or the satisfaction of other needs. The experiments carried out also demonstrate of the attachment system can help a robot adapt its own social behaviour to that of the human partners, as infants are thought to do during their development

Building a game scenario to encourage children with autism to recognize and label emotions using a humanoid robot

This paper presents an exploratory study in which children with autism interact with ZECA (Zeno Engaging Children with Autism). ZECA is a humanoid robot with a face covered with a material allowing the display of varied facial expressions. The study investigates a novel scenario for robot-assisted play, to help promoting labelling of emotions by children with autism spectrum disorders (ASD). The study was performed during three sessions with two boys diagnosed with ASD. The results obtained from the analysis of the children's behaviours while interacting with ZECA helped us improve several aspects of our game scenario such as the technical specificities of the game and its dynamics, and the experimental setup. The software produced for this study allows the robot to autonomously identify the answers of the child during the session. This automatic identification helped the fluidity of the game and freed the experimenter to participate in triadic interactions with the child. The evaluation of the game scenario that will be used in a future study was the main goal of this pilot study, rather than to quantify and evaluate the performance of the children. Overall, this exploratory study in teaching children about labelling emotions using a humanoid robot embedded in a game scenario demonstrated the possible positive outcomes this child-robot interaction can produce and highlighted the issues regarding data collection and their analysis that will inform future studies.Fundação para a Ciencia e Tecnologia in the scope of the project: PEst-OE/EEI/UI0319/2014. The authors are grateful to the Portuguese Foundation for the R&D project RIPD/ADA/109407/2009 and SFRH/BD/71600/2010 scholarshipinfo:eu-repo/semantics/publishedVersio

A pilot study using imitation and storytelling scenarios as activities for labelling emotions by children with autism using a humanoid robot

In this paper we present a child-robot interaction pilot study, focusing on recognizing and labelling emotions displayed by a humanoid robot. ZECA (Zeno Engaging Children with Autism) has a special skin covering its face which allows the display of facial expressions representing five emotions: joy, sadness, fear, anger, and surprise. These facial expressions were used in two different game scenarios, involving imitation and storytelling activities. The goal of these scenarios is to help the child acquire knowledge about different emotions and to improve their skill in recognizing them. The results show that these scenarios are appropriate for the goal established for this study, and positive behaviours concerning non-verbal communication were observed. This exploratory study demonstrated the possible positive outcomes this child-robot interaction can produce and highlighted the issues regarding data collection and their analysis that will inform future studies.This work has been supported by FCT Fundação para a Ciência e Tecnologia in the scope of the project: PEst-OE/EEI/UI0319/2014. The authors are grateful to the Portuguese Foundation (FCT) for the R&D project RIPD/ADA/109407/2009 and SFRH/BD/71600/2010 scholarship.info:eu-repo/semantics/publishedVersio

Arousal regulation and affective adaptation to human responsiveness by a robot that explores and learns a novel environment

Copyright © 2014 Hiolle, Lewis and Cañamero. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.In the context of our work in developmental robotics regarding robot-human caregiver interactions, in this paper we investigate how a "baby" robot that explores and learns novel environments can adapt its affective regulatory behavior of soliciting help from a "caregiver" to the preferences shown by the caregiver in terms of varying responsiveness. We build on two strands of previous work that assessed independently (a) the differences between two "idealized" robot profiles-a "needy" and an "independent" robot-in terms of their use of a caregiver as a means to regulate the "stress" (arousal) produced by the exploration and learning of a novel environment, and (b) the effects on the robot behaviors of two caregiving profiles varying in their responsiveness-"responsive" and "non-responsive"-to the regulatory requests of the robot. Going beyond previous work, in this paper we (a) assess the effects that the varying regulatory behavior of the two robot profiles has on the exploratory and learning patterns of the robots; (b) bring together the two strands previously investigated in isolation and take a step further by endowing the robot with the capability to adapt its regulatory behavior along the "needy" and "independent" axis as a function of the varying responsiveness of the caregiver; and (c) analyze the effects that the varying regulatory behavior has on the exploratory and learning patterns of the adaptive robot.Peer reviewe

Towards long-term social child-robot interaction: using multi-activity switching to engage young users

Social robots have the potential to provide support in a number of practical domains, such as learning and behaviour change. This potential is particularly relevant for children, who have proven receptive to interactions with social robots. To reach learning and therapeutic goals, a number of issues need to be investigated, notably the design of an effective child-robot interaction (cHRI) to ensure the child remains engaged in the relationship and that educational goals are met. Typically, current cHRI research experiments focus on a single type of interaction activity (e.g. a game). However, these can suffer from a lack of adaptation to the child, or from an increasingly repetitive nature of the activity and interaction. In this paper, we motivate and propose a practicable solution to this issue: an adaptive robot able to switch between multiple activities within single interactions. We describe a system that embodies this idea, and present a case study in which diabetic children collaboratively learn with the robot about various aspects of managing their condition. We demonstrate the ability of our system to induce a varied interaction and show the potential of this approach both as an educational tool and as a research method for long-term cHRI

Why should you care? : An arousal-based model of exploratory behavior for autonomous robots

The question of how autonomous robots could be part of our everyday life is of a growing interest. We present here an experiment in which an autonomous robot explores its environment and tries to familiarize itself with the features available using a neural-network-based architecture. The lack of stability of its learning structures increases the arousal level of the robot, pushing the robot to look for comfort from its caretaker to reduce the arousal. In this paper, we studied how the behavior of the caretaker influences the course of the robot exploration and learning experience by providing certain amount of comfort during this exploration. We then draw some conclusions on how to use this architecture together with related work, to enhance the adaptability of autonomous robots developmen