Personalization in Long-Term Human-Robot Interaction (PLOT-HRI19)

Long-term human-robot interaction is essential in many areas, such as for companion robots, rehabilitation, and education. However, interactions based on fixed collections of behaviors can become repetitive over time, causing user engagement to decrease after the novelty effect wears off. Personalization can help improve user engagement in long-term interactions, by adapting to the user’s personality, preferences, needs, or by recalling shared memories with the user. Moreover, personalizing the interaction can facilitate establishing rapport and trust between the user and the robot. However, long-term studies in human-robot interaction require a substantial amount of resources, especially if the robots are deployed “in the wild”, and do not always provide generalizable results due to the variability of subject needs, which makes it challenging for researchers to publish their results.

The “Personalization in Long-Term Human-Robot Interaction” workshop focuses on studies on adaptivity to users, context, environment, and tasks in long-term interactions in a variety of fields (e.g. companion robots, collaborative tasks, education, rehabilitation, elderly care). We intend to create a medium for researchers to share their work in progress, to introduce their preliminary results, and to share and discuss with other researchers about the problems they have encountered during their studies and their respective solutions. Consequently, the workshop will consist of presentations of the accepted papers through short (for 2 page papers) and full talks (for 3-4 pages), keynotes and interactive brainstorming activities to identify the problems that can arise in long-term HRI and find solutions using available technologies.

Hosted by Github Pages, 2019. Photo credit belongs to SoftBank Robotics Europe, Paris, France.