AUTHOR=Xue Ziheng , Elksnis Arturs , Wang Ning 

TITLE=Integrating large language models for intuitive robot navigation

JOURNAL=Frontiers in Robotics and AI

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2025.1627937

DOI=10.3389/frobt.2025.1627937

ISSN=2296-9144

ABSTRACT=Home assistance robots face challenges in natural language interaction, object detection, and navigation, mainly when operating in resource-constrained home environments, which limits their practical deployment. In this study, we propose an AI agent framework based on Large Language Models (LLMs), which includes EnvNet, RoutePlanner, and AIBrain, to explore solutions for these issues. Utilizing quantized LLMs allows the system to operate on resource-limited devices while maintaining robust interaction capabilities. Our proposed method shows promising results in improving natural language understanding and navigation accuracy in home environments, also providing a valuable exploration for deploying home assistance robots.