Data-Driven Natural Behavior Model Design with Large Language Models for Robotic-Animal Assisted Interventions (RAAI)

Abstract

Animal assisted intervention has been one of the effective natural therapeutic approaches, especially for individuals with autism. To increase the accessibility and reduce extra burden of care for the animals, Robotic-Animal Assisted Interventions (RAAI) has been proposed. However, the lack of natural behaviors is one of the key factors in limiting the feasibility with the current technology. This late-breaking report aims to build natural behavior models with data-driven approach, utilizing latest development of large language models (LLMs) to effectively analyze the data and build natural language-based models. Due to the reliance on LLM in this study, a key limitation is the lack of continuity in understanding. Frame images, as static representations, may not fully capture temporal dynamics. Future studies could address this limitation by integrating 3D-pose analysis, which would improve both continuity and contextual understanding.