HuCoM: A Model for Human Comfort Estimation in Personalized Human-Robot Collaboration

Abstract

Human comfort is significant in human-robot collaboration since it can influence the task efficiency and quality. In this paper, we propose a computational Human Comfort Model (HuCoM) to model and quantify the human comfort during human-robot collaborative manufacturing. Based on the defined primitive comfort rewards and combined comfort rewards, the HuCoM is developed with an incorporation of the static comfort model and the dynamic comfort model. We validate and evaluate the proposed model by several human-robot collaborative tasks via a YuMi robot.