This article discusses the potential of using interactive environments in autism therapy. We specifically address issues relevant to the Aurora project, which studies the possible role of autonomous, mobile robots as therapeutic tools for children with autism. Theories of mindreading, social cognition and imitation that informed the Aurora project are discussed and their relevance to the project is outlined. Our approach is put in the broader context of socially intelligent agents and interactive environments. We summarise results from trials with a (...) particular mobile robot. Finally, we draw some comparisons to research on interactive virtual environments in the context of autism therapy and education. We conclude by discussing future directions and open issues. (shrink)

Interactive robots are used increasingly not only in entertainment and service robotics, but also in rehabilitation, therapy and education. The work presented in this paper is part of the Aurora project, rooted in assistive technology and robot-human interaction research. Our primary aim is to study if robots can potentially be used as therapeutically or educationally useful ‘toys’. In this paper we outline the aims of the project that this study belongs to, as well as the specific qualitative contextual perspective that (...) is being used. We then provide an in-depth evaluation, in part using Conversation Analysis, of segments of trials where three children with autism interacted with a robot as well as an adult. We focus our analysis primarily on joint attention which plays a fundamental role in human development and social understanding. Joint attention skills of children with autism have been studied extensively in autism research and therefore this behaviour provides a relevant focus for our study. In the setting used, joint attention emerges from natural and spontaneous interactions between a child and an adult. We present the data in the form of transcripts and photo stills. The examples were selected from extensive video footage for illustrative purposes, i.e. demonstrating how children with autism can respond to the changing behaviour of their co-participant, i.e. the experimenter. Furthermore, our data shows that the robot provides a salient object, or mediator for joint attention. The paper concludes with a discussion of implications of this work in the context of further studies with robots and children with autism within the Aurora project, as well as the potential contribution of robots to research into the nature of autism. (shrink)

This article presents a novel set of ten play scenarios for robot-assisted play for children with special needs. This set of scenarios is one of the key outcomes of the IROMEC project that investigated how robotic toys can become social mediators, encouraging children with special needs to discover a range of play styles, from solitary to collaborative play. The target user groups in the project were children with Mild Mental Retardation,1 children with Severe Motor Impairment and children with Autism. The (...) play scenarios were developed against specific educational and therapeutic objectives that were discussed with panels of experts in various countries, during several user panel meetings for each of the above mentioned target user groups. These objectives were classified with reference to the ICF-CY, the International Classification of Functioning – version for Children and Youth. The article presents a detailed description of the play scenarios, each with its relevant educational and therapeutic objectives in five key developmental areas. While the play scenarios described in this paper originally were developed for and tested with the above user groups and with the IROMEC robot, the play scenarios can potentially be applied to other user groups and to a wide range of other applications involving human-robot interaction using different robotic toys. Keywords: human-robot interaction; assistive technology; play scenarios; autism; mild mental retardation; sever motor impairment; assisted play. (shrink)

This article studies the impact of a robot’s appearance on interactions involving four children with autism. This work is part of the Aurora project with the overall aim to support interaction skills in children with autism, using robots as ‘interactive toys’ that can encourage and mediate interactions. We follow an approach commonly adopted in assistive robotics and work with a small group of children with autism. This article investigates which robot appearances are suitable to encourage interactions between a robot and (...) children with autism. The children’s levels of interaction with and response to different appearances of two types of robots are compared: a small humanoid doll, and a life-sized ‘Theatrical Robot’. The small humanoid robot appeared either as a human-like ‘pretty doll’ or as a ‘robot’ with plain features. The Theatrical Robot was presented either as an ordinary human, or with plain clothing and a featureless, masked face. The results of these trials clearly indicate the children’s preference in their initial response for interaction with a plain, featureless robot over the interaction with a human-like robot. In the case of the life-size Theatrical Robot, the response of children towards the plain/robotic robot was notably more social and pro-active. Implications of these results for our work on using robots as assistive technology for children with autism and their possible use in autism research are discussed. (shrink)

This article presents results from a multidisciplinary research project on the integration and transfer of language knowledge into robots as an empirical paradigm for the study of language development in both humans and humanoid robots. Within the framework of human linguistic and cognitive development, we focus on how three central types of learning interact and co-develop: individual learning about one's own embodiment and the environment, social learning (learning from others), and learning of linguistic capability. Our primary concern is how these (...) capabilities can scaffold each other's development in a continuous feedback cycle as their interactions yield increasingly sophisticated competencies in the agent's capacity to interact with others and manipulate its world. Experimental results are summarized in relation to milestones in human linguistic and cognitive development and show that the mutual scaffolding of social learning, individual learning, and linguistic capabilities creates the context, conditions, and requisites for learning in each domain. Challenges and insights identified as a result of this research program are discussed with regard to possible and actual contributions to cognitive science and language ontogeny. In conclusion, directions for future work are suggested that continue to develop this approach toward an integrated framework for understanding these mutually scaffolding processes as a basis for language development in humans and robots. (shrink)

This paper examines interaction involving a child with an Autistic Spectrum Disorder, a humanoid robot and a co-present adult. In this paper data from one child (collected as part of the ROBOSKIN project) is analysed in order to evaluate the potential contributions of a conversation analytic perspective to the examination of data relating to socio-emotional reciprocity. The paper argues for the value of treating all interaction as potentially relevant, looking without carefully pre-defined target behaviours and examining behaviour within its specific (...) sequence of interaction. Adopting this approach, the paper suggests, enables noticings and observations that might not be available from perspectives that rely on the coding of pre-specified behaviours in isolation. Treating all interaction as potentially relevant brought into view interactions that might otherwise be dismissed or ignored – because they occurred before, or after, the trial itself. Being informed by the value of unmotivated looking – rather than pre-specified coding schemes – enabled highly relevant behaviour that was not anticipated within the trials to be analysed. Finally, seeing sequence as important meant that behaviours were appreciated in their intricate detail, enabling a more precise understanding than might be available if they were considered separately from that sequential environment. Keywords: autism; assessment; autistic spectrum disorder; experiment; conversation analysis; interaction; humanoid robot; sequences; sequence of interaction; socio-emotional reciprocity. (shrink)

This paper examines interaction involving a child with an Autistic Spectrum Disorder, a humanoid robot and a co-present adult. In this paper data from one child is analysed in order to evaluate the potential contributions of a conversation analytic perspective to the examination of data relating to socio-emotional reciprocity. The paper argues for the value of treating all interaction as potentially relevant, looking without carefully pre-defined target behaviours and examining behaviour within its specific sequence of interaction. Adopting this approach, the (...) paper suggests, enables noticings and observations that might not be available from perspectives that rely on the coding of pre-specified behaviours in isolation. Treating all interaction as potentially relevant brought into view interactions that might otherwise be dismissed or ignored – because they occurred before, or after, the trial itself. Being informed by the value of unmotivated looking – rather than pre-specified coding schemes – enabled highly relevant behaviour that was not anticipated within the trials to be analysed. Finally, seeing sequence as important meant that behaviours were appreciated in their intricate detail, enabling a more precise understanding than might be available if they were considered separately from that sequential environment. Keywords: autism; assessment; autistic spectrum disorder; experiment; conversation analysis; interaction; humanoid robot; sequences; sequence of interaction; socio-emotional reciprocity. (shrink)

This paper presents a novel methodological approach of how to design, conduct and analyse robot-assisted play. This approach is inspired by nondirective play therapy. The experimenter participates in the experiments, but the child remains the main leader for play. Besides, beyond inspiration from non-directive play therapy, this approach enables the experimenter to regulate the interaction under specific conditions in order to guide the child or ask her questions about reasoning or affect related to the robot. This approach has been tested (...) in a long-term study with six children with autism in a school setting. An autonomous robot with zoomorphic, dog-like appearance was used in the studies. The children’s progress was analyzed according to three dimensions, namely, Play, Reasoning and Affect. Results from the case-study evaluations have shown the capability of the method to meet each child’s needs and abilities. Children who mainly played solitarily progressively experienced basic imitation games with the experimenter. Children who proactively played socially progressively experienced higher levels of play and constructed more reasoning related to the robot. They also expressed some interest in the robot, including, on occasion, affect. Keywords: Human–Robot Interaction, Robot-Mediated Therapy, Robot-Assisted Play, Non-Directive Play Therapy, Assistive Technology, Autism, Children. (shrink)

On reviewing the literature regarding acceptance and trust in human-robot interaction (HRI), there are a number of open questions that needed to be addressed in order to establish effective collaborations between humans and robots in real-world applications. In particular, we identified four principal open areas that should be investigated to create guidelines for the successful deployment of robots in the wild. These areas are focused on: (1) the robot’s abilities and limitations; in particular when it makes errors with different severity (...) of consequences, (2) individual differences, (3) the dynamics of human-robot trust, and (4) the interaction between humans and robots over time. In this paper, we present two very similar studies, one with a virtual robot with human-like abilities, and one with a Care-O-bot 4 robot. In the first study, we create an immersive narrative using an interactive storyboard to collect responses of 154 participants. In the second study, 6 participants had repeated interactions over three weeks with a physical robot. We summarise and discuss the findings of our investigations of the effects of robots’ errors on people’s trust in robots for designing mechanisms that allow robots to recover from a breach of trust. In particular, we observed that robots’ errors had greater impact on people’s trust in the robot when the errors were made at the beginning of the interaction and had severe consequences. Our results also provided insights on how these errors vary according to the individuals’ personalities, expectations and previous experiences. (shrink)

The study of imitation and other mechanisms of social learning is an exciting area of research for all those interested in understanding the origin and the nature of animal learning in a social context. Moreover, imitation is an increasingly important research topic in Artificial Intelligence and social robotics which opens up the possibility of individualized social intelligence in robots that are part of a community, and allows us to harness not only individual learning by the single robot, but also the (...) acquisition of new skills by observing other members of the community. After an introduction to the main research issues in research on imitation in various fields, we motivate the particular focus of this work, namely the correspondence problem. We describe Action Learning for Imitation via Correspondences between Embodiments, an implemented generic framework for solving the correspondence problem between differently embodied robots. Alice enables a robotic agent to learn a behavioral repertoire suitable to performing a task by observing a model agent. Importantly, the model agent could possibly possess a different type of body, e.g. a different number of limbs or joints, a different height, different sensors, a different basic action repertoire, etc. Previously, in a test-bed where the agents differed according to their possible movement patterns, we demonstrated that the character of imitation achieved will depend on the granularity of subgoal matching, and on the metrics used to evaluate success. In our current work, we implemented Alice in a new test-bed called Rabit where simple simulated robotic arm agents use various metrics for evaluating success according to actions, states, effects, or weighted combinations. We examine the roles of synchronization, looseness of perceptual matching, and of proprioceptive matching by a series of experiments. Also, we study how Alice copes with changes in the embodiment of the imitator during learning. Our simulation results suggest that synchronization and loose perceptual matching allow for faster acquisition of behavioral compentencies at low error rates. Social learning plays a role as a replication mechanism for behaviors and results in variability when the transmitted behavior differs from the model’s behavior, thus providing the evolutionary substrate for culture and its pre-cursors. Social learning in robotics could therefore serve as the basis for culture in societies whose members include artificial agents. We address the use of imitative social learning mechanisms like Alice for transmission of skills between robots, and give first examples of transmission of a skill despite differences in embodiment of agents involved. In the particular setup, transmission occurs through a chain, as well as emerging in cyclic arrangements of robots. These simple examples demonstrate that by using social learning and imitation, cultural transmission is possible among robots, even in heterogeneous groups of robots. (shrink)

We describe an exploratory case study about the applicability of different robotic platforms in an educational context with a child with Down syndrome. The robotic platforms tested are the humanoid robot KASPAR and the mobile robotic platform IROMEC. During the study we observed the effects KASPAR and IROMEC had in helping the child with the development and improvement of her social skills while playing different interactive games with the robots. Conceptually similar play scenarios were performed with both robots and the (...) behaviour of the child was monitored during her interactions with them. (shrink)

Identifying links between human personality and attributed robot personality is a relatively new area of human–robot interaction. In this paper we report on an exploratory study that investigates human and robot personality traits as part of a human–robot interaction trial. The trials took place in a simulated living-room scenario involving 28 participants and a human-sized robot of mechanical appearance. Participants interacted with the robot in two task scenarios relevant to a ‘robot in the home’ context. It was found that participants’ (...) evaluations of their own personality traits are related to their evaluations of the robot’s personality traits. The statistical analysis of questionnaire data yields several statistically significant results: Participants do not tend to assign their personality traits to match the robots’, For individual personality traits, participants rated themselves as having stronger personality characteristics compared to the robot, Specific significant correlations were found between participants’ and robot personality traits, and Significant group differences for participant gender, age and technological background are highlighted. The results are discussed in light of developing personalized robot companions. (shrink)

Research into robotic social learning, especially that concerned with imitation, often focuses at differing ends of a spectrum from observational learning at one end to following or matched-dependent behaviour at the other. We study the implications and differences that arise when carrying out experiments both at the extremes and within this spectrum. Physical Khepera robots with minimal sensory capabilities are used, and after training, experiments are carried out where an imitating robot perceives the dynamic movement behaviours of another model robot (...) carrying a light source. It learns the movement behaviour of the model by either statically observing the model, dynamically observing the model or by following the model. It finally re-enacts the learnt behaviour. We compare the results of these re-enactments and illustrate the differences and trade-offs that arise between static observational and reactive following learning methods. We also consider circumstances where, for this robotic embodiment, dynamic observation has both advantages and disadvantages when compared to static observation. We conclude by discussing the implications that arise from using and combining these types of social learning. (shrink)

This article discusses the potential of using interactive environments in autism therapy. We specifically address issues relevant to the Aurora project, which studies the possible role of autonomous, mobile robots as therapeutic tools for children with autism. Theories of mindreading, social cognition and imitation that informed the Aurora project are discussed and their relevance to the project is outlined. Our approach is put in the broader context of socially intelligent agents and interactive environments. We summarise results from trials with a (...) particular mobile robot. Finally, we draw some comparisons to research on interactive virtual environments in the context of autism therapy and education. We conclude by discussing future directions and open issues. (shrink)

How do we perceive robots practising a task that we have taught them? While learning, human trainees usually provide nonverbal cues that reveal their level of understanding and interest in the task. Similarly, nonverbal social cues of trainee robots that can be interpreted naturally by humans can enhance robot learning. In this article, we investigated a scenario in which a robot is practising a physical task in front of the human teachers, who were asked to assume that they had previously (...) taught the robot to perform that task. Through an online experiment with 167 participants, we examined the effects of different gaze patterns and arm movements with multiple speeds and various kinds of pauses on human teachers’ perception of different attributes of the robot. We found that the perception of a trainee robot’s attributes can be systematically affected by its behaviours. Findings of this study can inform designing more successful nonverbal social interactions for intelligent robots. (shrink)

The study of imitation and other mechanisms of social learning is an exciting area of research for all those interested in understanding the origin and the nature of animal learning in asocial context. Moreover, imitation is an increasingly important research topic in Artificial Intelligence and social robotics which opens up the possibility ofindividualized social intelligencein robots that are part of a community, and allows us to harness not only individual learning by the single robot, but also the acquisition of new (...) skills by observing other members of the community. After an introduction to the main research issues in research on imitation in various fields, we motivate the particular focus of this work, namely thecorrespondence problem. We describeAction Learning for Imitation via Correspondences between Embodiments, an implemented generic framework for solving the correspondence problem between differently embodied robots. Alice enables a robotic agent to learn a behavioral repertoire suitable to performing a task by observing a model agent. Importantly, the model agent could possibly possess a different type of body, e.g. a different number of limbs or joints, a different height, different sensors, a different basic action repertoire, etc. Previously, in a test-bed where the agents differed according to their possible movement patterns, we demonstrated that the character of imitation achieved will depend on the granularity of subgoal matching, and on the metrics used to evaluate success.In our current work, we implemented Alice in a new test-bed calledRabitwhere simple simulated robotic arm agents use various metrics for evaluating success according to actions, states, effects, or weighted combinations.We examine the roles ofsynchronization,looseness of perceptual matching, and ofproprioceptive matchingby a series of experiments. Also, we study how Alice copes withchanges in the embodimentof the imitator during learning. Our simulation results suggest thatsynchronizationandloose perceptual matchingallow for faster acquisition of behavioral compentencies at low error rates.Social learning plays a role as areplicationmechanism for behaviors and results invariabilitywhen the transmitted behavior differs from the model’s behavior, thus providing theevolutionary substrate for cultureand its pre-cursors. Social learning in robotics could therefore serve as the basis for culture in societies whose members include artificial agents. We address the use of imitative social learning mechanisms like Alice for transmission of skills between robots, and give first examples of transmission of a skill despite differences in embodiment of agents involved. In the particular setup, transmission occurs through a chain, as well as emerging in cyclic arrangements of robots. These simple examples demonstrate that by using social learning and imitation,cultural transmissionis possible among robots, even in heterogeneous groups of robots. (shrink)

We describe an exploratory case study about the applicability of different robotic platforms in an educational context with a child with Down syndrome. The robotic platforms tested are the humanoid robot KASPAR and the mobile robotic platform IROMEC. During the study we observed the effects KASPAR and IROMEC had in helping the child with the development and improvement of her social skills while playing different interactive games with the robots. Conceptually similar play scenarios were performed with both robots and the (...) behaviour of the child was monitored during her interactions with them. (shrink)

This paper describes our general framework for the investigation of how human gestures can be used to facilitate the interaction and communication between humans and robots. Two studies were carried out to reveal which “naturally occurring” gestures can be observed in a scenario where users had to explain to a robot how to perform a home task. Both studies followed a within-subjects design: participants had to demonstrate how to lay a table to a robot using two different methods — utilizing (...) only gestures or gestures and speech. The first study enabled the validation of the COGNIRON coding scheme for human gestures in Human–Robot Interaction. Based on the data collected in both studies, an annotated video corpus was produced and characteristics such as frequency and duration of the different gestural classes have been gathered to help capture requirements for the designers of HRI systems. The results from the first study regarding the frequencies of the gestural types suggest an interaction between the order of presentation of the two methods and the actual type of gestures produced. However, the analysis of the speech produced along with the gestures did not reveal differences due to ordering of the experimental conditions. The second study expands the issues addressed by the first study: we aimed at extending the role of the interaction partner by introducing some positive acknowledgement of the participants’ activity. The results show no significant differences in the distribution of gestures between the two explanation methods, in contrast to the previous study. Implications for HRI are discussed focusing on issues relevant for the design of the robot’s communication skills to support the interaction loop with humans in home scenarios. (shrink)

Identifying links between human personality and attributed robot personality is a relatively new area of human–robot interaction. In this paper we report on an exploratory study that investigates human and robot personality traits as part of a human–robot interaction trial. The trials took place in a simulated living-room scenario involving 28 participants and a human-sized robot of mechanical appearance. Participants interacted with the robot in two task scenarios relevant to a ‘robot in the home’ context. It was found that participants’ (...) evaluations of their own personality traits are related to their evaluations of the robot’s personality traits. The statistical analysis of questionnaire data yields several statistically significant results: Participants do not tend to assign their personality traits to match the robots’, For individual personality traits, participants rated themselves as having stronger personality characteristics compared to the robot, Specific significant correlations were found between participants’ and robot personality traits, and Significant group differences for participant gender, age and technological background are highlighted. The results are discussed in light of developing personalized robot companions. (shrink)

In recent years the possibility of using humanoid robots to perform interviews with children has been explored in a number of studies. This paper details a study in which a potential real-world user trialled a Robot-Mediated Interviewing system with children to establish if this approach could realistically be used in a real-world context. In this study a senior educational psychologist used the humanoid robot Kaspar to interview ten primary school children about a video they had watched prior to the interview. (...) We conducted a pre and post interview with the educational psychologist before and after using the system to establish how the system worked for him and the perceived potential for real-world applications. The educational psychologist successfully used the system to interview the children and believed that principally using a small humanoid robot to interview children could be useful in a real-world setting provided the system was developed further. (shrink)

In recent years the possibility of using humanoid robots to perform interviews with children has been explored in a number of studies. This paper details a study in which a potential real-world user trialled a Robot-Mediated Interviewing system with children to establish if this approach could realistically be used in a real-world context. In this study a senior educational psychologist used the humanoid robot Kaspar to interview ten primary school children about a video they had watched prior to the interview. (...) We conducted a pre and post interview with the educational psychologist before and after using the system to establish how the system worked for him and the perceived potential for real-world applications. The educational psychologist successfully used the system to interview the children and believed that principally using a small humanoid robot to interview children could be useful in a real-world setting provided the system was developed further. (shrink)

To date research investigating the potential of Robot-Mediated Interviews has focused on establishing how children respond to robots in an interview scenario. In order to test if an RMI approach would work in a real world setting, it is important to establish what the experts would require from such a system. To determine the needs of such expert users we conducted three user panels with groups of potential real world users to gather their views of our current system and find (...) out what they would require for the system to be useful to them. The user groups consisted of specialist police officers, intermediaries, educational specialists and healthcare specialists. To our knowledge this is the first article investigating user needs for Robot-Mediated Interviews. Due to the novelty of this area, the work presented in this paper is exploratory in nature. The results provide valuable insights into what real world users would need from a Robot-Mediated Interviewing system. Our findings will contribute to future research and technology development in the domain of RMI in particular, and child-robot interaction in general. (shrink)

To date research investigating the potential of Robot-Mediated Interviews has focused on establishing how children respond to robots in an interview scenario. In order to test if an RMI approach would work in a real world setting, it is important to establish what the experts would require from such a system. To determine the needs of such expert users we conducted three user panels with groups of potential real world users to gather their views of our current system and find (...) out what they would require for the system to be useful to them. The user groups consisted of specialist police officers, intermediaries, educational specialists and healthcare specialists. To our knowledge this is the first article investigating user needs for Robot-Mediated Interviews. Due to the novelty of this area, the work presented in this paper is exploratory in nature. The results provide valuable insights into what real world users would need from a Robot-Mediated Interviewing system. Our findings will contribute to future research and technology development in the domain of RMI in particular, and child-robot interaction in general. (shrink)