Personalized clothing recommendation by a social robot

Abstract

Social robots can assist individuals with performing a number of different daily tasks. One such task, which has not been extensively explored, is suggesting appropriate clothing to an individual. This paper presents a novel, autonomous, clothing recommendation system that employs social robots. The proposed system can autonomously recommend options, from a user's wardrobe, that are personalized to an activity at hand. The novelty of the system lies in its ability to learn from the individual users' preferences over time. The learning-based personalization feature allows the system to assist new users as well as adapt to users whose preferences change over time. Human-robot interaction studies were conducted to assess both the performance of the overall system as well as its potential long-term adaptability.