The evolving field of human-robot interaction (HRI) necessitates that we better understand how social robots operate and interact with humans. This scoping review provides an overview of about 300 research works focusing on the use of the NAO robot from 2010 to 2020. This study presents one of the most extensive and inclusive pieces of evidence on the deployment of the humanoid NAO robot and its global reach. Unlike most reviews, we provide both qualitative and quantitative results regarding how NAO is being used and what has been achieved so far. We analyzed a wide range of theoretical, empirical, and technical contributions that provide multidimensional insights, such as general trends in terms of application, the robot capabilities, its input and output modalities of communication, and the human-robot interaction experiments that featured NAO (e.g. number and roles of participants, design, and the length of interaction). Lastly, we derive from the review some research gaps in current state-of-the-art and provide suggestions for the design of the next generation of social robots.

Social robots are increasingly being used as a mediator between a therapist and a child in autism therapy studies. In this context, most behavioural interventions are typically short-term in nature. This paper describes a long-term study that was conducted with 11 children diagnosed with either Autism Spectrum Disorder (ASD) or ASD in co-occurrence with Attention Deficit Hyperactivity Disorder (ADHD). It uses a quantitative analysis based on behavioural measures, including engagement, valence, and eye gaze duration. Each child interacted with a robot on several occasions in which each therapy session was customized to a child’s reaction to robot behaviours. This paper presents a set of robot behaviours that were implemented with the goal to offer a variety of activities to be suitable for diverse forms of autism. Therefore, each child experienced an individualized robot-assisted therapy that was tailored according to the therapist’s knowledge and judgement. The statistical analyses showed that the proposed therapy managed to sustain children’s engagement. In addition, sessions containing familiar activities kept children more engaged compared to those sessions containing unfamiliar activities. The results of the interviews with parents and therapists are discussed in terms of therapy recommendations. The paper concludes with some reflections on the current study as well as suggestions for future studies.

This research occurred in a special context where Kazakhstan's recent decision to switch from Cyrillic to the Latin-based alphabet has resulted in challenges connected to teaching literacy, addressing a rare combination of research hypotheses and technical objectives about language learning. Teachers are not necessarily trained to teach the new alphabet, and this could result in a challenge for children with learning difficulties. Prior research studies in Human-Robot Interaction (HRI) have proposed the use of a robot to teach handwriting to children (Hood et al., 2015; Lemaignan et al., 2016). Drawing on the Kazakhstani case, our study takes an interdisciplinary approach by bringing together smart solutions from robotics, computer vision areas, and educational frameworks, language, and cognitive studies that will benefit diverse groups of stakeholders. In this study, a human-robot interaction application is designed to help primary school children learn both a newly-adopted script and also its handwriting system. The setup involved an experiment with 62 children between the ages of 7–9 years old, across three conditions: a robot and a tablet, a tablet only, and a teacher. Based on the paradigm—learning by teaching—the study showed that children improved their knowledge of the Latin script by interacting with a robot. Findings reported that children gained similar knowledge of a new script in all three conditions without gender effect. In addition, children's likeability ratings and positive mood change scores demonstrate significant benefits favoring the robot over a traditional teacher and tablet only approaches.

This paper presents a patient-centered interaction design of Robot-Assisted Therapy or Robot-Assisted Play (RAP) applications for children with a diverse form of Autism Spectrum Disorder (ASD) combined with Attention Deficit Hyperactivity Disorder (ADHD). Through our iterative evaluation process based on observations of fourteen children over several sessions and interviews with their parents, we continuously refined the behaviors of a humanoid robot NAO that are now ready to be used for research on Robot-Assisted Therapy. This paper also reports the design of RAP methodology that might be helpful in assimilating iterative input from stakeholders such as children, parents and therapists to customize technology for other populations with special needs.