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SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots

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SIGVerse: A Cloud-Based VR Platform for Research on Multimodal Human-Robot Interaction.

Tetsunari Inamura^1,2, Yoshiaki Mizuchi¹

¹National Institute of Informatics, Tokyo, Japan.

Frontiers in Robotics and AI

|June 17, 2021

Summary

This study introduces a novel research platform integrating virtual reality (VR) and cloud computing to streamline Human-Robot Interaction (HRI) experiments. The platform facilitates cost-effective, immersive HRI research and development, enhancing social intelligence evaluation.

Keywords:

dataset of interaction robot competition social and embodied intelligence software platform virtual reality

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Area of Science:

Robotics
Virtual Reality
Human-Robot Interaction

Background:

Human-Robot Interaction (HRI) research demands significant experimental design and practice time.
Virtual Reality (VR) offers potential solutions by reducing costs, standardizing conditions, visualizing complex scenarios, and enabling natural teleoperation.
Existing VR tools for HRI lack comprehensive frameworks and haven't fully leveraged cloud computing integration.

Purpose of the Study:

To propose an integrated VR and cloud computing research platform for HRI.
To provide a flexible and reusable system for HRI research.
To address the need for comprehensive tools in VR-assisted HRI.

Main Methods:

Developed a real-time bridging mechanism between the Robot Operating System (ROS) and Unity.
Integrated VR and cloud technologies to create a unified research platform.
Utilized the platform in practical HRI scenarios and case studies.

Main Results:

Successfully created a flexible and reusable HRI research platform.
Demonstrated the system's feasibility through three case studies, including RoboCup@Home.
Validated the platform's usefulness for developing and evaluating social intelligence in multimodal HRI.

Conclusions:

The proposed platform effectively integrates VR and cloud technologies for HRI research.
The system streamlines experimental design and execution, reducing time and cost.
The platform shows significant potential for advancing the field of social intelligence in HRI.