Interaction Studies - Volume 22, Issue 2, 2021

Abstract

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 (i.e., participants), 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 (e.g., confidence and eagerness to learn) can be systematically affected by its behaviours. Findings of this study can inform designing more successful nonverbal social interactions for intelligent robots.

Abstract

Recent research showed the potential benefits of robot-assisted therapy in treating children with Autism Spectrum Disorder. These children often have some form of Intellectual Disability (ID) too, but this has mainly been neglected by previous robotics research. This article presents an empirical evaluation of robot-assisted imitation training, where the child imitated the robot, integrated into the Treatment and Education of Autistic and related Communication handicapped Children (TEACCH) program. The sample included six hospitalized children with different levels of ID, from mild to profound. We applied mixed methods to assess their progress, during treatment and three months later. Results show increased Gross Motor Imitation skills in the children, except for those with profound ID and the therapists’ positive attitude towards the humanoid robot. Furthermore, the therapists suggest how a robot could be used to autonomously collect and analyze the information obtained in the rehabilitation training for a continuous evaluation of the participants.

Abstract

In this paper, we explore interaction history as a particular source of pressure for achieving emergent compositional communication in multi-agent systems. We propose a training regime implementing template transfer, the idea of carrying over learned biases across contexts. In the presented method, a sender-receiver dyad is first trained with a disentangled pair of objectives, and then the receiver is transferred to train a new sender with a standard objective. Unlike other methods (e.g. the obverter algorithm), the template transfer approach does not require imposing inductive biases on the architecture of the agents. We experimentally show the emergence of compositional communication using topographical similarity, zero-shot generalization and context-independence as evaluation metrics. The presented approach is connected to an important line of work in semiotics and developmental psycholinguistics: it supports a conjecture that compositional communication is scaffolded on simpler communication protocols.

Abstract

Research in social robotics is commonly focused on designing robots that imitate human behavior. While this might increase a user’s satisfaction and acceptance of robots at first glance, it does not automatically aid a non-expert user in naturally interacting with robots, and might hurt their ability to correctly anticipate a robot’s capabilities. We argue that a faulty mental model, that the user has of the robot, is one of the main sources of confusion. In this work, we investigate how communicating technical concepts of robotic systems to users affect their mental models, and how this can increase the quality of human-robot interaction. We conducted an online study and investigated possible ways of improving users’ mental models. Our results underline that communicating technical concepts can form an improved mental model. Consequently, we show the importance of consciously designing robots that express their capabilities and limitations.

This article reviews Philosophy of Language978-1-107-48062-9

This article reviews Using Corpus Methods to Triangulate Linguistic Analysis9781138082540