Human Action Recognition for Social Robots

Abstract

Social assistive robotics is at the forefront of the effort for ensuring independent living and inclusion, especially for the elderly and vulnerable members of the population. We consider that to be proactive is a core requirement of such robotic systems. One key aspect of being proactive is to understand what the user is doing. We explored the task of human action recognition in the context of a social robotic platform based on a framework that we proposed in earlier work. We implemented a processing pipeline specific to this task then collected a dataset using a Pepper robot. The proposed domain adaptation method to increase performance of the method showed promising results.