An Ontology-Driven System for Diversity-Aware Human-RobotInteraction Using LLMs

This extended abstract presents a novel system for diversity-aware autonomous conversations using Large Language Models (LLMs). Leveraging a cloud-based architecture and an ontology-driven knowledge base, the system adapts interactions to a wide range of user characteristics. Experiments in both controlled settings and real-world case studies demonstrate the system's effectiveness in managing complex interactions and sustaining user engagement across various environments.