The advent of sophisticated robotics and AI technology makes sending humans into hazardous and distant environments to carry out inspections increasingly avoidable. Being able to send a robot, rather than a human, into a nuclear facility or deep space is very appealing. However, building these robotic systems is just the start and we still need to carry out a range of verification and validation tasks to ensure that the systems to be deployed are as safe and reliable as possible. Based on our experience across three research and innovation hubs within the UK’s “Robots for a Safer World” programme, we present an overview of the relevant techniques and challenges in this area. As the hubs are active across nuclear, offshore, and space environments, this gives a breadth of issues common to many inspection robots.

This opinion paper discusses how human–robot interaction (HRI) methodologies can be robustly developed by drawing on insights from fields outside of HRI that explore human–other interactions. The paper presents a framework that draws parallels between HRIs, and human–human, human–animal and human–object interaction literature, by considering the morphology and use of a robot to aid the development of robust HRI methodologies. The paper then briefly presents some novel empirical work as proof of concept to exemplify how the framework can help researchers define the mechanism of effect taking place within specific HRIs. The empirical work draws on known mechanisms of effect in animal-assisted therapy, and behavioural observations of touch patterns and their relation to individual differences in caring and attachment styles, and details how this trans-disciplinary approach to HRI methodology development was used to explore how an interaction with an animal-like robot was impacting a user. In doing so, this opinion piece outlines how useful objective, psychological measures of social cognition can be for deepening our understanding of HRI, and developing richer HRI methodologies, which take us away from questions that simply ask ‘Is this a good robot?’, and closer towards questions that ask ‘What mechanism of effect is occurring here, through which effective HRI is being performed?’ This paper further proposes that in using trans-disciplinary methodologies, experimental HRI can also be used to study human social cognition in and of itself. This article is part of the theme issue ‘From social brains to social robots: applying neurocognitive insights to human–robot interaction’.

Animal-Computer Interaction (ACI) is a new and quickly developing discipline, which is closely related to HCI and is making reference to some of its theoretical frameworks and research methodologies. The first edition of the Workshop on Research Methods in ACI (RM4ACI) was co-located with the Third International Conference on Animal-Computer Interaction, which took place in Milton-Keynes, UK in November 2016. This paper presents an overview of the workshop, including insights from discussions on some of the challenges faced by the ACI community as it works to develop ACI as a discipline, and on important opportunities for cross-fertilization between HCI and ACI that the HCI community could consider.

There is an increasing interest in considering, measuring, and implementing trust in human-robot interaction (HRI). New avenues in this field include identifying social means for robots to influence trust, and identifying social aspects of trust such as a perceptions of robots’ integrity, sincerity or even benevolence. However, questions remain regarding robots’ authenticity in obtaining trust through social means and their capacity to increase such experiences through social interaction with users. We propose that the dyadic model of HRI misses a key complexity: a robot’s trustworthiness may be contingent on the user’s relationship with, and opinion of, the individual or organisation deploying the robot (termed here, Deployer). We present a case study in three parts on researching HRI and a LEGO^® Serious^® Play focus group on care robotics to indicate how Users’ trust towards the Deployer can affect trust towards robots and robotic research. Our Social Triad model (User, Robot, Deployer) offers novel avenues for exploring trust in a social context.

This document presents the outcomes of the Dagstuhl Seminar “Roadmap for Responsible Robotics,” held in September 2023 at the Leibniz Center for Informatics, Schloss Dagstuhl, Germany. The seminar brought together researchers from the fields of robotics, computer science, social and cognitive sciences, and philosophy with the aim of charting a path toward improving responsibility in robotic systems. Through intensive interdisciplinary discussions centered on the various values at stake as robotics increasingly integrates into human life, the participants identified key priorities to guide future research and regulatory efforts. The resulting road map outlines actionable steps to ensure that robotic systems coevolve with human societies, promoting human agency and humane values rather than undermining them. Designed for diverse stakeholders—researchers, policy makers, industry leaders, practitioners, nongovernmental organizations (NGOs), and civil society groups—this road map provides a foundation for collaborative efforts toward responsible robotics.