Multi-human spatial social pattern understanding for a multi-modal robot through nonverbal social signals

Abstract

For service robots to be able to enter a multi-human office environment, it is important to find a group of human users' social patterns and then to provide a proper service to them in time. Usually, human users' social patterns are represented in terms of nonverbal social signals. In this paper, a new integrated approach on recognizing multi-human social signals is proposed. Specifically, the nonverbal social signals are detected by a laser range finder and a RGB-D camera and are processed to find the multi-human (spatial) social patterns. Those recognized patterns are then applied to human-to-human, human-to-robot or multi-human-to-robot interactive formation. Experimental results shows that our robot successfully recognizes the aforementioned users' social patterns followed by appropriate services.