Trust plays a major role when introducing interactive robots into people’s personal spaces, which, in large part, depends on how they perceive the robot. This paper presents the initial results of an investigation into the perception of robot agency as a potential factor influencing trust. We manipulated a robot’s agency to see how trust would change as a result. Our preliminary results indicate age as a confounding factor while we did not find differences when priming robot autonomy.

We present a new typology for classifying signals from robots when they communicate with humans. For inspiration, we use ethology, the study of animal behaviour and previous efforts from literature as guides in defining the typology. The typology is based on communicative signals that consist of five properties: the origin where the signal comes from, the deliberateness of the signal, the signal's reference, the genuineness of the signal, and its clarity (i.e., how implicit or explicit it is). Using the accompanying worksheet, the typology is straightforward to use to examine communicative signals from previous human-robot interactions and provides guidance for designers to use the typology when designing new robot behaviours.

This paper presents an investigation into the effectiveness of introducing explicit causal explanations in a child-robot interaction setting to help children with autism improve their Visual Perspective Taking (VPT) skills. A sample of ten children participated in three sessions with a social robot on different days, during which they played several games consisting of VPT tasks. In some of the sessions, the robot provided constructive feedback to the children by giving causal explanations related to VPT; other sessions were control sessions without explanations. An analysis of the children’s learning progress revealed that they improved their VPT abilities faster when the robot provided causal explanations. However, both groups ultimately reach a similar ratio of correct answers in later sessions. These findings suggest that providing causal explanations using a social robot can be effective to teach VPT to children with autism. This study paves the way for further exploring a robot’s ability to provide causal explanations in other educational scenarios.

The research presented in this paper investigates the feasibility of using humanoid robots like Kaspar as assistive tools in Speech, Language and Communication (SLC) therapy for children with learning disabilities. The study aims to answer two research questions: RQ1. Can a social robot be used to improve SLC skills of children with learning disabilities? RQ2. What is the measurable impact of interacting with a humanoid robot on children with learning disability and SLC needs? A co-creation approach was followed, three therapeutic educational games were developed and implemented on the Kaspar robot in collaboration with experienced SLC experts. Twenty children from two different special educational needs schools participated in the games in 9 sessions over a period of 3 weeks. Results showed significant improvement in participants’ SLC skills – i.e. language comprehension and production skills– over the intervention. Findings of this research affirms feasibility, suggesting that this type of robotic interaction is the right path to follow to help the children improve their SLC skills.

Children with Autism Spectrum Disorder (ASD) often struggle with visual perspective taking (VPT) skills and the understanding that others might have viewpoints and perspectives that are different from their own; i.e., the ability to understand that two or more people looking at the same object from different positions might not see the same thing. The understanding of VPT can be improved by introducing explicit causal explanations in the interactions involving autistic children. Moreover, the use of social robots can help autistic children improve their social skills. We present a retrospective study with Kaspar, a humanoid social robot specifically designed to interact with children with ASD, which aims to define the initial protocol for a study on the effect of causal explanation in VPT provided by Kaspar. To this end, we investigate in which scenarios causal explanations, provided either by researchers or by Kaspar, contribute substantially to the child’s understanding of VPT. The results have helped us identify multiple interaction categories that benefit from causal explanation. We have used these results in order to define new interaction games that benefit from causal explanations. These are now progressing through usability assessment experiments.

As home robot companions become more common, it is important to understand what types of tasks are considered critical to perform correctly. This paper provides working definitions of task criticality, physical and cognitive tasks with respect to robot task performance. Our research also suggests that although people's perceptions of task criticality is independent of robot appearances, their expectation that a robot performs tasks correctly is affected by it's appearance.

How do mistakes made by a robot affect its trustworthiness and acceptance in human-robot collaboration? We investigate how the perception of erroneous robot behavior may influence human interaction choices and the willingness to cooperate with the robot by following a number of its unusual requests. For this purpose, we conducted an experiment in which participants interacted with a home companion robot in one of two experimental conditions: (1) the correct mode or (2) the faulty mode. Our findings reveal that, while significantly affecting subjective perceptions of the robot and assessments of its reliability and trustworthiness, the robot's performance does not seem to substantially influence participants' decisions to (not) comply with its requests. However, our results further suggest that the nature of the task requested by the robot, e.g. whether its effects are revocable as opposed to irrevocable, has a significant impact on participants' willingness to follow its instructions.

This paper presents a study of the readability of dog-inspired visual communication signals in a human-robot interaction scenario. This study was motivated by specially trained hearing dogs which provide assistance to their deaf owners by using visual communication signals to lead them to the sound source. For our human-robot interaction scenario, a robot was used in place of a hearing dog to lead participants to two different sound sources. The robot was preprogrammed with dog-inspired behaviors, controlled by a wizard who directly implemented the dog behavioral strategy on the robot during the trial. By using dog-inspired visual communication signals as a means of communication, the robot was able to lead participants to the sound sources (the microwave door, the front door). Findings indicate that untrained participants could correctly interpret the robot's intentions. Head movements and gaze directions were important for communicating the robot's intention using visual communication signals.