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.

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

Campilii, Elena
Primo
;
Perpetuini, David;Merla, Arcangelo;Cardone, Daniela
Ultimo
2025-01-01

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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11564/865253
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