Using Mixed Reality for Safe Physical Human-Robot Interaction

Abstract

Ensuring safety in shared human-robot workspaces is a critical challenge in modern industrial environments. This paper explores a novel approach that leverages a mixed reality (MR) headset and digital twin technology to enhance human-robot safety. This system integrates real-time data from the physical environment into a digital twin. This enables interactions between both tele-operated and autonomous robots. The digital twin feeds data into a speed and separation monitoring (SSM) algorithm, which dynamically adjusts the speed of the robot or stops it to prevent collisions with human workers. To validate the accuracy and reliability (standard deviation) of the MR-based implementation, the system error is measured against data obtained from a motion capture system. The results demonstrate the effectiveness of using digital twins in conjunction with MR for improved safety in collaborative workspaces. This paper details the methodology, implementation, and evaluation of the system, highlighting its potential impact on the future of human robot interaction (HRI).