HuBotVerse: Towards Internet of Human and Intelligent Robotic Things with a Digital Twin-Based Mixed Reality Framework

Although the Internet of Robotic Things (IoRT) has enhanced the productivity of robotic systems in conjunction with the Internet of Things (IoT), it does not inherently support seamless human-robot collaboration.

This paper presents HuBotVerse, a unified framework designed to foster the evolution of the Internet of Human and Intelligent Robotic Things (IoHIRT). HuBotVerse is advantageous due to its unique features, including security, user-friendliness, compatibility, manageability, and its open-source nature. Moreover, this framework can easily integrate various Human-Robot Interaction (HRI) interfaces to facilitate collaborative control between humans and robots. Here, we emphasize a Digital Twin-Based Mixed Reality (MR) interface, which enhances teleoperation efficiency by offering users an intuitive and immersive way to interact.  

To evaluate the effectiveness of HuBotVerse, we conducted user studies based on a pick-and-place task. Feedback was gathered through questionnaires, complemented by a quantitative analysis of key performance metrics, user experience, and the NASA Task Load Index (NASA-TLX). Results indicate that the fusion of MR and HuBotVerse within a comprehensive framework significantly improves the efficiency and user experience of teleoperation. Moreover, the follow-up questionnaires reflect the advantages of the HuBotVerse framework in terms of evident user-friendliness, manageability, and usability in homecare or healthcare applications. 

Open-Source Practice and Project Description

We establish this website to enable multiple users to share knowledge and collaborate in a user-friendly editing environment. 

The website will include several subpages, including Tutorials, Videos (for case studies), Resources (for compatible robotic things that can be integrated to the system), Codes&Data, Team, and Q&A.

We encourage technicians and researchers to release the codes which are built upon this platform.

The open-source codes for low-level control of robotic platforms can be reused by many researchers. Researchers can co-create learning materials for robotics projects, and work together to develop customized user interfaces collaboratively for their experiments.

The videos for hardware system professional training will be recorded and shared in the tutorial 'section'. 

The proposed online lab system can enhance the efficiency of both research and education.