Exploring Empathic Human-Robot Collaboration

Abstract

Robots are increasingly integrated into human environments across various domains, progressively emphasizing human well-being. Moreover, the empathic behavior exhibited by robots is essential for enhancing human well-being. It requires the robots to understand the physical, mental, and emotional human state to display reciprocal empathic behavior, both non-trivial for robots. Although progress has been made in understanding individual aspects of the human state, an effort to jointly model the human state is still missing, especially for psychological and physiological states. To this end, we explore the human digital twin (HDT) paradigm, an extension of digital twins, to introduce empathy in human-robot systems. Existing HDT frameworks are domain/context-specific (or too broad) and require further exploration for empathy context. We propose an HDT framework specifically tailored for empathic human-robot collaboration (HRC). Additionally, we present a proof-of-concept HDT model based on our proposed framework, which we qualitatively evaluated using an HRC scenario-based case study.