User detection, tracking and recognition in robot assistive care scenarios

Abstract

The field of assistive robotics is gaining traction in both research as well as industry communities. However, capabilities of existing robotic platforms still require improvements in order to implement meaningful human-robot interactions. We report on the design and implementation of an external system that significantly augments the person detection, tracking and identification capabilities of the Pepper robot. We perform a qualitative analysis of the improvements achieved by each system module under different interaction conditions and evaluate the whole system on hand of a scenario for elderly care assistance.