Enhancing Human-Robot Interaction Using Generative Artificial Intelligence: The Case of The NAO Robot

This paper presents a novel interface enabling seamless human-robot interaction by integrating the NAO social robot with OpenAI’s generative language model, ChatGPT. The interface, developed in Python, allows users to interact verbally with the NAO robot, which responds with context-aware and natural language outputs generated by ChatGPT. The system architecture includes a graphical user interface and dual-script integration to overcome compatibility issues between Python 2.7 (for NAO) and Python 3.x (for OpenAI API). Experimental evaluations demonstrated an average response time of 1.37 seconds per 10 tokens and confirmed stable performance under moderate background noise conditions. These results highlight the potential of combining generative AI with social robots to enhance engagement and communication in real-world applications, including education, healthcare, and assistive robotics.

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Publication Details

Published
2025-08-07
DOI
https://doi.org/10.1109/acdsa65407.2025.11165865
Primary Topic
Robotics and Automated Systems
Type
article
Field-Weighted Citation Impact
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article

Enhancing Human-Robot Interaction Using Generative Artificial Intelligence: The Case of The NAO Robot

Arcangelo Merla, David Perpetuini, Daniela Cardone, Elena Campilii
Robotics and Automated Systems
article

Enhancing Human-Robot Interaction Using Generative Artificial Intelligence: The Case of The NAO Robot

Arcangelo Merla, David Perpetuini, Daniela Cardone, Elena Campilii
article en

Abstract

This paper presents a novel interface enabling seamless human-robot interaction by integrating the NAO social robot with OpenAI’s generative language model, ChatGPT. The interface, developed in Python, allows users to interact verbally with the NAO robot, which responds with context-aware and natural language outputs generated by ChatGPT. The system architecture includes a graphical user interface and dual-script integration to overcome compatibility issues between Python 2.7 (for NAO) and Python 3.x (for OpenAI API). Experimental evaluations demonstrated an average response time of 1.37 seconds per 10 tokens and confirmed stable performance under moderate background noise conditions. These results highlight the potential of combining generative AI with social robots to enhance engagement and communication in real-world applications, including education, healthcare, and assistive robotics.

University of Chieti-Pescara (IT)
Openalex Percentile: Top 67%
Robotics and Automated Systems
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