Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.494557
Title: Facilitating play between children with autism and an autonomous robot
Author: Francois, Dorothee C. M.
Awarding Body: University of Hertfordshire
Current Institution: University of Hertfordshire
Date of Award: 2009
Availability of Full Text:
Access from EThOS:
Access from Institution:
Abstract:
This thesis is part of the Aurora project, an ongoing long-term project investigating the potential use of robots to help children with autism overcome some of their impairments in social interaction, communication and imagination. Autism is a spectrum disorder and children with autism have different abilities and needs. Related research has shown that robots can play the role of a mediator for social interaction in the context of autism. Robots can enable simple interactions, by initially providing a relatively predictable environment for play. Progressively, the complexity of the interaction can be increased. The purpose of this thesis is to facilitate play between children with autism and an autonomous robot. Children with autism have a potential for play but often encounter obstacles to actualize this potential. Through play, children can develop multidisciplinary skills, involving social interaction, communication and imagination. Besides, play is a medium for self-expression. The purpose here is to enable children with autism to experience a large range of play situations, ranging from dyadic play with progressively better balanced interaction styles, to situations of triadic play with both the robot and the experimenter. These triadic play situations could also involve symbolic or pretend play. This PhD work produced the following results: • A new methodological approach of how to design, conduct and analyse robotassisted play was developed and evaluated. This approach draws inspiration from non-directive play therapy where the child is the main leader for play and the experimenter participates in the play sessions. I introduced a regulation process which enables the experimenter to intervene under precise conditions in order to: i) prevent the child from entering or staying in repetitive behaviours, ii) provide bootstrapping that helps the child reach a situation of play she is about to enter and iii) ask the child questions dealing with affect or reasoning about the robot. This method has been tested in a long-term study with six children with autism. Video recordings of the play sessions were analysed in detail according to three dimensions, namely Play, Reasoning and Affect. Results have shown the ability of this approach to meet each child’s specific needs and abilities. Future work may develop this work towards a novel approach in autism therapy. • A novel and generic computational method for the automatic recognition of human-robot interaction styles (specifically gentleness and frequency of touch interaction) in real time was developed and tested experimentally. This method, the Cascaded Information Bottleneck Method, is based on an information theoretic approach. It relies on the principle that the relevant information can be progressively extracted from a time series with a cascade of successive bottlenecks sharing the same cardinality of bottleneck states but trained successively. This method has been tested with data that had been generated with a physical robot a) during human-robot interactions in laboratory conditions and b) during child-robot interactions in school. The method shows a sound recognition of both short-term and mid-term time scale events. The recognition process only involves a very short delay. The Cascaded Information Bottleneck is a generic method that can potentially be applied to various applications of socially interactive robots. • A proof-of-concept system of an adaptive robot was demonstrated that is responsive to different styles of interaction in human-robot interaction. Its impact was evaluated in a short-term study with seven children with autism. The recognition process relies on the Cascaded Information Bottleneck Method. The robot rewards well-balanced interaction styles. The study shows the potential of the adaptive robot i) to encourage children to engage more in the interaction and ii) to positively influence the children’s play styles towards better balanced interaction styles. It is hoped that this work is a step forward towards socially adaptive robots as well as robot-assisted play for children with autism.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.494557  DOI: Not available
Keywords: Human-robot interaction ; Robot-assisted play ; Autism ; Socially adaptive robots ; Machine learning ; Assistive technology
Share: