A Tool for Organizing Key Characteristics of Virtual, Augmented, and Mixed Reality for Human-Robot Interaction Systems: Synthesizing VAM-HRI Trends and Takeaways

TL;DR

This paper introduces TOKCS, a tool that categorizes key features of VAM-HRI systems, improving consistency and capturing new characteristics to better analyze trends and guide future research in the field.

Contribution

The work develops TOKCS, a novel framework that discretizes continuous scales and adds new characteristics for better classification of VAM-HRI systems.

Findings

TOKCS effectively classifies VAM-HRI systems from recent literature.

Application of TOKCS reveals emerging trends and future directions.

The tool enhances understanding of VAM-HRI system characteristics.

Abstract

Frameworks have begun to emerge to categorize Virtual, Augmented, and Mixed Reality (VAM) technologies that provide immersive, intuitive interfaces to facilitate Human-Robot Interaction. These frameworks, however, fail to capture key characteristics of the growing subfield of VAM-HRI and can be difficult to consistently apply due to continuous scales. This work builds upon these prior frameworks through the creation of a Tool for Organizing Key Characteristics of VAM-HRI Systems (TOKCS). TOKCS discretizes the continuous scales used within prior works for more consistent classification and adds additional characteristics related to a robot's internal model, anchor locations, manipulability, and the system's software and hardware. To showcase the tool's capability, TOKCS is applied to the ten papers from the fourth VAM-HRI workshop and examined for key trends and takeaways. These trends highlight the expressive capability of TOKCS while also helping frame newer trends and future work recommendations for VAM-HRI research.