PERSEO at RO-MAN 2023, IEEE International Conference on Robot and Human Interactive Communication

On August 28-31, four early-stage researchers and their supervisors, Silvia Rossi, Alessandra Rossi and Alessandro Di Nuovo, participated in the 32nd IEEE International Conference on Robot and Human Interactive Communication that was hold in Busan, South Korea.

Georgios Angelopoulos presented the paper “Unveiling the Learning Curve: Enhancing Transparency in Robot’s Learning with Inner Speech and Emotions”. In this work, they present a study where users observe a robot endowed with three distinct emotional/behavioural mechanisms for conveying transparent information about its learning process. The proposed mechanisms use inner speech, emotions, and a combination of the two communication styles (hybrid). To assess and evaluate the transparency of these behavioural models, a between-subject study was conducted with 108 participants. Results indicate that the people’s perception of the robot’s warmth dimension increased when it utilized a hybrid model to explain its learning state. Additionally, increased transparency was observed when the robot used inner speech during the learning process.

Francesco Vigni presented the paper “Sweet Robot O’Mine – How a Cheerful Robot Boosts Users’ Performance in a Game Scenario”. In this work, they endowed a robot with two personality behavioural patterns: one more antagonist and other-comparative and the other one more agreeable and self-comparative. They conducted a user study where N = 66 participants played a game with a robot displaying the two multimodal communication styles. Their 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.

Dimitri Lacroix presented the paper “Pimp my language! The influence of robot customization duration on psychological ownership and trust”. This work presents an online experiment, they investigated whether actual time invested in choosing options (i.e., words that a robot would learn) and implementing them (i.e., defining the words to a robot in the individual’s own terms) influenced psychological ownership and trust towards the robot. They observed that the time invested in choosing options slightly decreased perceived control and psychological ownership over the robot. This might be due to task difficulty, which hints at the role of perceived self-efficacy as a determinant of psychological ownership. No effect of time spent in implementing the chosen words by defining them has been found.

Mehdi Hellou presented the paper “Bayesian Theory of Mind for False Belief Understanding in Human-Robot Interaction”. This work presents an artificial intelligence system capable of detecting false beliefs, a critical skill for social agents involved in collaborative tasks or caring for elderly people in retirement homes. They rely on a probabilistic Theory of Mind model to detect when a human has false beliefs with the purpose of driving the decision-making process of a collaborative robot. In particular, they recreate an established psychology experiment involving the search for a toy that can be secretly displaced by a malicious individual. The results that they have obtained in simulated experiments show that the agent is able to predict human mental states and detect when false beliefs have arisen. They then explored the set-up in a real-world human interaction to assess the feasibility of such an experiment with a humanoid social robot.

Francesco Vigni also co-organized the Workshop “WARN: Weighting the benefits of Autonomous Robot persoNalization”, which focused on the benefits and drawbacks of personalisation and behavioural adaptation in social HRI. In particular, this workshop brought together a multidisciplinary group of researchers from areas including, but not limited to, psychology, neuroscience, computer science, robotics, and sociology, to share and discuss current approaches to empowering social assistive robots with adaptive and learning capabilities in order to foster research and development of robotic solutions specifically designed for meeting the individual’s unique needs. During this half-day workshop, Angelopoulos also actively participated in the discussions presenting his PhD work.