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LLM-enhanced Interactions in Human-Robot Collaborative Drawing with Older Adults

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Abstract

The goal of this study is to identify factors that support and enhance older adults’ creative experiences in human-robot co-creativity. Because the research into the use of robots for creativity support with older adults remains underexplored, we carried out an exploratory case study. We took a participatory approach and collaborated with professional art educators to design a course "Drawing with Robots" for adults aged 65 and over. The course featured human-human and human-robot drawing activities with various types of robots. We observed collaborative drawing interactions, interviewed participants on their experiences, and analyzed collected data. Findings show that participants preferred acting as curators, evaluating creative suggestions from the robot in a teacher or coach role. When we enhanced a robot with a multimodal Large Language Model (LLM), participants appreciated its spoken dialogue capabilities. They reported however, that the robot’s feedback sometimes lacked an understanding of the context, and sensitivity to their artistic goals and preferences. Our findings highlight the potential of LLM-enhanced robots to support creativity and offer future directions for advancing human-robot co-creativity with older adults.
Original languageEnglish
Title of host publication2025 34th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)
PublisherIEEE Press
Pages700-707
Number of pages7
DOIs
Publication statusPublished - 3 Nov 2025

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