Affective Human-Robot Interaction
AHRI 2023: Second Workshop on Affective Human-Robot Interaction at ACII 2023
In recent years, robotic applications have seen an increasing real-world deployment. It is common in these applications that a user interacts directly with a robot. In such Human-Robot Interaction (HRI), trust and mutual adaptation is established and maintained through a positive social relationship between the robot and the human interactor, and relies on the perceived competence of a robot on the social-emotional dimension. How a user perceives a robot's social intelligence and their social relationship with the robot can have a direct influence on the outcomes of an HRI system. Moreover, in many HRI applications, social-emotional interaction with the intended users is the main goal of the system or a core strategy to achieve the desired outcomes. Such affective HRI applications require emotion-awareness and social-emotional competence in the robot's functions to deliver acceptable services.
Following the success in 2022, the second AHRI workshop will continue to provide a communication and collaboration platform for researchers working on affective computing, HRI, social robotics, and AI and robotics application. In alignment with the ACII 2023’s theme in “Affective Computing: Context and Multimodality”, we especially welcome submissions on HRI in multimodal and naturalistic interaction contexts. This workshop will focus on discussing the following topics:
How to adaptively/accurately perceive unimodal or multimodal affective human behaviour in HRI under particular interaction context.
How to efficiently generate natural and affective robot behaviour in HRI that is appropriate for the interaction context.
How to measure the benefits and outcomes of affective HRI applications with a user-centred and contextualised approach.
Our workshop will bring together researchers from the disciplines of HRI, affective computing, healthcare, and various related fields to facilitate discussion and future collaborations. We expect that this will greatly advance the benefits of affective computing systems for healthcare applications and affective HRI research.