This study explores the complex dynamics between humans and robots, focusing on how emotional states influence proxemics. We conducted a user study using a standard mobile robot to investigate whether emotions elicited from a loudspeaker, affect human perception of robot proximity. Based on previous research on Human-Human Interaction (HHI), we analysed participants’ responses to robots displaying different behaviours. Participants observed the robot’s approach while experiencing positive or negative emotions. Our findings suggest that emotional states induced by external stimuli can affect participants’ perception of robot proximity. In detail, the results indicate that while comfortable stopping distances were unaffected by participants’ emotional state, individuals who experienced positive emotions judged the same proxemics distance used while performing an avoidance behaviour to be more acceptable compared to the case of negative emotions. This study describes the extent to which our emotions can alter the perception of robot behaviours, ultimately affecting our acceptance of these novel social agents.

The development of social robots with advanced conversational capabilities aiming to engage humans in natural interactions has recently surged. This paper investigates the dynamic aspect of Human-Robot Interaction (HRI), focusing on the regulation of interpersonal distance based on human emotion. Through a user study with a humanoid robot, we explore how participants perceive and respond to rule-based versus randomly generated robot behaviours in adjusting inter-personal space during an unconstrained conversation. Results suggest that participants perceive the robot using rule-based behaviours as more socially competent and adaptable to human behaviour and emotions compared to the random ones. These findings highlight the importance of considering subtle non-verbal cues and adapting robot behaviour based on human emotions to improve the quality of HRI, and consequently facilitate the successful integration of human natural nuances in robots.

The ability to impact the attitudes and behaviours of others is a key aspect of human-human interaction. The same capability is a desideratum in human-robot interaction when it can have an impact on healthy behaviours. The robot’s interaction style plays a significant role in achieving effective communication, leading to better outcomes, improved user experience, and overall enhanced robot performance. Nonetheless, little is known about how different robots’ communication styles impact users’ performance and decision-making. In this article, we build upon previous work, in which a robot was endowed with two personality behavioural patterns: one more antagonist and other-comparative and the other one more agreeable and self-comparative. We conducted a user study where N = 66 participants played a game with a robot displaying the two multimodal communication styles. Our results indicated that i) participants’ decision-making was not influenced by the designed robot’s communication styles, ii) participants who interacted with the agreeable robot performed better in the game, and iii) the more participants are knowledgeable about robots, the lower they performed in the game.

When navigating in a shared environment, the extent to which robots are able to effectively use signals for coordinating with human behaviors can ameliorate dissatisfaction and increase acceptance. In this paper, we present an online video study to investigate whether familiar acoustic signals can improve the legibility of a robot’s navigation behavior. We collected the responses of 120 participants to evaluate their perceptions of a robot that communicates with one of the three used non-verbal navigational cues (an acoustic signal, an acoustic in pair with a visual signal, and a dissimilar frequency acoustic signal). Our results showed a significant legibility improvement when the robot used both light and acoustic signals to communicate its intentions compared to using only the same acoustic sound. Additionally, our findings highlighted that people also perceived differently the robot’s intentions when they were expressed through two frequencies of the mere sound. The results of this work suggest a paradigm that can help the development of mobile service robots in public spaces.