On the impact of robot personalization on human-robot interaction: A review
Jinyu Yang, Camille Vindolet, Julio Rogelio Guadarrama Olvera, Gordon Cheng
TL;DR
The paper addresses how robot personalization affects human-robot interaction in socially assistive robots across healthcare, education, and daily-life tasks. It surveys a range of personalization strategies from predefined dialogue to adaptive, multimodal policies and links them to concrete use cases and technologies. Key findings show generally positive effects on engagement, trust, and learning outcomes, while highlighting privacy, safety, and ethical concerns as underexplored risks. The work provides a foundation for designing personalized HRI systems and identifies important directions for future research and policy to ensure responsible deployment.
Abstract
This study reviews the impact of personalization on human-robot interaction. Firstly, the various strategies used to achieve personalization are briefly described. Secondly, the effects of personalization known to date are discussed. They are presented along with the personalized parameters, personalized features, used technology, and use case they relate to. It is observed that various positive effects have been discussed in the literature while possible negative effects seem to require further investigation.