Do You Understand Me, DUM-E? Enabling Seamless Human-Robot Communication Through Augmented Reality

This paper introduces an Augmented Reality (AR) system that facilitates seamless intent communication between a human and a collaborative robot during complex assembly tasks. This system leverages a Unity-ROS pipeline to integrate AR with multimodal input and output capabilities, providing a rich, interactive interface for Human-Robot Interaction (HRI). To evaluate the system’s effectiveness, a series of user studies were conducted with participants performing assembly tasks under different communication scenarios involving different interaction modes and intent interpretation feedback. The effects of the AR system on participants’ task performance and user satisfaction were analyzed, indicating that the AR-enabled multimodal interface significantly improves communication clarity, reduces errors, and enhances overall task efficiency compared to traditional methods with no AR feedback. Immediate visual feedback significantly reduces task completion times and error rates. Higher levels of user confidence and trust in the robot were observed when visual feedback was provided, highlighting the importance of transparency in robot actions.

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Publication Details

Published
2024-10-21
DOI
https://doi.org/10.1109/ismar-adjunct64951.2024.00153
Citations
4
Primary Topic
Robotics and Automated Systems
Type
article
Field-Weighted Citation Impact
1.31

Funders

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article

Do You Understand Me, DUM-E? Enabling Seamless Human-Robot Communication Through Augmented Reality

Mohsen Moghaddam, Stacy Marsella, Akhil Ajikumar
4 citations
Robotics and Automated Systems
1.31
article

Do You Understand Me, DUM-E? Enabling Seamless Human-Robot Communication Through Augmented Reality

Mohsen Moghaddam, Stacy Marsella, Akhil Ajikumar
article en
4 citations

Abstract

This paper introduces an Augmented Reality (AR) system that facilitates seamless intent communication between a human and a collaborative robot during complex assembly tasks. This system leverages a Unity-ROS pipeline to integrate AR with multimodal input and output capabilities, providing a rich, interactive interface for Human-Robot Interaction (HRI). To evaluate the system’s effectiveness, a series of user studies were conducted with participants performing assembly tasks under different communication scenarios involving different interaction modes and intent interpretation feedback. The effects of the AR system on participants’ task performance and user satisfaction were analyzed, indicating that the AR-enabled multimodal interface significantly improves communication clarity, reduces errors, and enhances overall task efficiency compared to traditional methods with no AR feedback. Immediate visual feedback significantly reduces task completion times and error rates. Higher levels of user confidence and trust in the robot were observed when visual feedback was provided, highlighting the importance of transparency in robot actions.

Universidad del Noreste (MX)
National Science Foundation
Openalex Percentile: Top 18%
Robotics and Automated Systems
1.31
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