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Social robots will be soon deployed in large public spaces populated by many people. This scenario differs from personal domestic robots, since it is characterized by multiple short-term interactions with unknown people rather than by a long-term interaction with the known user. In particular, short-term interactions with people in a public area must be effective, personalized and socially acceptable. In this paper, we present the design and implementation of an Human-Robot Interaction module that allows to personalize short-term multi-modal interactions. This module is based on explicit representation of social norms and thus provides a high degree of variability in the personalization of the interactions, maintaining easy extendibility and scalability. The module is designed within the framework of the COACHES project and some implementation details are provided in order to demonstrate its feasibility and capabilities.

Personalized Short-Term Multi-modal Interaction for Social Robots Assisting Users in Shopping Malls