The road to successful HRI: trust, acceptance, ethics, social signals and AI

This Special Issue is based on the conjunction of the workshops SCRITA (Trust, Acceptance and Social Cues in Human Robot Interaction) and TRAITS (The Road to a successful HRI: AI, Trust and ethicS) respectively organised at IEEE RO-MAN and ACM/IEEEHRI 2021 conferences. The design of natural human-robot dynamics is a key aspect for ensuring a successful and efficient lasting human-robot interaction (HRI). In particular, it is expected that a robot deployed in human populated environments not only needs to be able to successfully complete a task, involving perception, reasoning and decision-making of other agents and the surroundings, but also needs to show social intelligence to engage people in effective and natural interactions. In such interactions, robots and people need to be able to cooperate to reach a joint goal, which can only be achieved if people accept and trust robots to complete their task and prevent any potential harm (emotional or physical) to people, the environment and themselves. The agents involved need to correctly interpret each other's behaviour, and act accordingly. Finally, several studies have shown that socially aware robots are perceived more positively by people in social contexts and situations. Robots, therefore, should be able to understand and use people's direct and indirect modes of communication, such as verbal and non-verbal cues. Moreover, robots should be able to adapt their behaviours to satisfy people's needs (such as personality, emotions, preferences, habits), and incorporating reactive and predictive meta-cognition models to reason about the situational context (such as its own erroneous behaviours) and provide socially acceptable behaviours. This special issue will explore successful HRI from a multidisciplinary perspective and shape the design of robots, so that robots: 1) autonomously sense and react to the situation, people and the environment by integrating artificial intelligence (AI) techniques 2) such that people feel comfortable to interact with robots 3) and trust them to safely reach intended outcomes, and 4) by respecting ethical and legal principles. Submissions are invited from leading researchers in the fields including, but not limited, to the following topics of interest: ● Impact of social cues on trust in human-robot interaction ● The impact of social robots on acceptance in HRI ● Measuring trust in human-robot interaction ● Trust violation and recovery mechanism in HRI ● Effects of humans’ acceptance on trust of robots ● Humans sense of control and trust in robots ● Trust and assistive robotics ● Overtrust in robots ● Antecedent of trust and human-robot trust ● Enhancing humans trust in robots ● User profiling and trust in human-robot interaction ● Evaluation of human-robot interaction quality ● Human factors affecting successful HRI ● Mental models in HRI ● XAI in HRI ● Trustworthy AI ● Legal frameworks for trustworthy robotics ● Ethics implications in HRI