User Profiling Based Proactive Interaction Manager for Adaptive Human-robot Interaction

Abstract

Proactive interaction is a highly researched topic in the robotics arena. By using its proactive ability, a robot can decide intelligently in specific situations, taking particular attributes into account, to offer a certain service to the user. We propose a proactive interaction manager to suggest suitable reading suggestions to the user. User profiling is used as a tool to identify the nature and preferences of each user. A user’s profile is based on multiple attributes that determine whether a user chooses a particular genre for reading. This is developed as a strategy to identify the preferences of users. Since the user’s preferences may change over time, an algorithm to adaptively provide reading suggestions to the user considering their changes in preferences is also proposed. We conducted two experiments to evaluate the performance of the proposed proactive interaction manager. The results of the experiments show that the proposed approach is satisfactory for a domestic service robot based application.