Towards Real-World Data Supported XR Training of Trustworthy Human-Robot Interaction in a Risky Environment

摘要

This paper presents the first phase of an experiment on utilizing eXtended Reality to develop a training and testing system for a humanoid robot in an unconventional or risky environment. The risky aspect of the environment is air pollution, and the robot should provide corresponding trustworthy assistance to humans occupying it. The paper discusses the human robot interaction and the role of eXtended Reality in creating virtual environments where it can be evaluated. It also deals with air pollution data acquisition from a real environment and analyzes the data obtained.