Increasingly researchers are looking outside of normal communication channels (such as video and audio) to provide additional forms of communication or interaction between a human and a robot, or a robot and its environment. Amongst the new channels being investigated is the detection of touch using infrared, proprioceptive and temperature sensors. Our work aims at developing a system that can detect natural touch or interaction coming from children playing with a robot, and adapt to this interaction. This paper reports trials carried out using Roball, a spherical mobile robot, demonstrating how sensory data patterns can be identified in human-robot interaction, and exploited for achieving behavioral adaptation. The experimental methodology used for these trials is reported, which validated the hypothesis that human interaction can not only be perceived from proprioceptive sensors on-board a robotic platform, but that this perception has the ability to lead to adaptation.

The study presented in this paper explored people's perceptions and attitudes towards the idea of a future robot companion for the home. A human-centred approach was adopted using questionnaires and human-robot interaction trials to derive data from 28 adults. Results indicated that a large proportion of participants were in favour of a robot companion and saw the potential role as being an assistant, machine or servant. Few wanted a robot companion to be a friend. Household tasks were preferred to child/animal care tasks. Humanlike communication was desirable for a robot companion, whereas humanlike behaviour and appearance were less essential. Results are discussed in relation to future research directions for the development of robot companions.

This paper proposes a technique for quantitatively describing and analysing robot-human interactions in terms of low-level behavioural criteria (so-called micro-behaviours). In order to demonstrate the usefulness of this technique, we describe a case study that was conducted as part of the Aurora project where we develop robotic toys as therapeutic tools for children with autism. In this project we made explicit choices of how to assess robot-human interaction and how to study the impact of interaction. Results of a comparative study with autistic children are shown where we focus on eye gaze behaviour. The results point out common tendencies as well as clear differences among the children, important information for future development of robots in the Aurora project. We propose that this technique is applicable to a wide range of application areas that involve robot-human interactions. The work presented in this paper is intended to open up a discussion on appropriate techniques to systematically assess robot-human interactions. Such research is important for the development of robots in human-inhabited environments.