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Embodied Generative AI Art for Enhanced Human-Robot Interaction Through a Human-Centric LLM-Guided Robotic Arm Drawing System

  • Shengyuan Xie
  • , Eduardo Benitez Sandoval
  • , Khaja Ahmed Shaik
  • , Francisco Cruz
  • UNSW Sydney

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Generative AI is transforming the way humans interact with robots by integrating language-driven comprehension with embodied execution. While recent research leveraging large language models (LLMs) to enhance communication between humans and machines has shown significant progress, the exploration of integrating LLMs with robots to assist users in creating real-world artistic works remains challenging. This research introduces a novel GENAI-driven intelligent robotic arm drawing system. We fine-tuned GPT-3.5 Turbo to better capture meaningful information from conversations with users and output precise drawing commands, which are directly fed into the fine-tuned Stable Diffusion model to generate desired images. A UFactory xArm equipped with an end-effector holding a drawing pen is deployed and controlled by a speed control algorithm to perform accurate drawing movements based on AI-generated images. Our proposed framework facilitates enhanced HRI experiences with a focus on drawing tasks, effectively embodying the capabilities of generative AI in the field of artistic creation and enabling users to engage deeply in the process of using AI for art creation in real-world environments.

Original languageEnglish
Title of host publicationHRI 2025 - Proceedings of the 2025 ACM/IEEE International Conference on Human-Robot Interaction
PublisherIEEE Computer Society
Pages1727-1730
Number of pages4
ISBN (Electronic)9798350378931
DOIs
StatePublished - 2025

Publication series

NameACM/IEEE International Conference on Human-Robot Interaction
ISSN (Electronic)2167-2148

Keywords

  • Art
  • Generative AI
  • Human-Robot Interaction
  • LLMs
  • Robotic Arm

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