Communication in Human-Robot Interaction

Abstract

Purpose of Review To present the multi-faceted aspects of communication between robot and humans (HRI), putting in evidence that it is not limited to language-based interaction, but it includes all aspects that are relevant in communication among physical beings, exploiting all the available sensor channels. Recent Findings For specific purposes, machine learning algorithms could be exploited when data sets and appropriate algorithms are available. Summary Together with linguistic aspects, physical aspects play an important role in HRI and make the difference with respect to the more limited human-computer interaction (HCI). A review of the recent literature about the exploitation of different interaction channels is presented. The interpretation of signals and the production of appropriate communication actions require to consider psychological, sociological, and practical aspects, which may affect the performance. Communication is just one of the functionalities of an interactive robot and, as all the others, will need to be benchmarked to support the possibility for social robots to reach a real market.

Design and Development of a Scale for Evaluating the Acceptance of Social Robotics for Older People: The Robot Era Inventory

“…For this purpose, the HRI may be supported by multichannel sensory features, which generally include auditory, visual, and tactile capabilities. Also, the esthetical parts of the robots are relevant for communication, such as eyes, dimensions, and shape (Bonarini, 2020 ). To appreciate and measure the quality of the HRI, key elements of the interaction should be defined during the setup of any experimentation or the design of a new product: the human, the robot, their interaction, and the context (Collins, 2019 ).…”

Communicative Robot Signals: Presenting a New Typology for Human-Robot Interaction

“…Activity or inactivity, words or silence all have message value" [58, p. 30]. One model by Bonarini [2] examines the channels of hearing, sight, and touch that are available to humans for communicating with robots and suggests to use machine-learning techniques to teach robot behaviours and then benchmark their performance [2]. This can provide a starting point to explore communication channels.…”

An Architecture for Safe Child–Robot Interactions in Autism Interventions

“…Interaction modalities range from the communication channel that is used. Typically, these channels consist of speech and optical attributes of interaction, and the signals that produced should be cohesive and effective in order to maintain a sufficient level of interaction [41]. Therefore, interaction modalities of SAR consist of vocal cues, speech, and sound, which are involved in the hearing channel, and lights and expressions, which form the visual channel.…”