Embodied Intelligence in Mining: Leveraging Multi-Modal Large Language Models for Autonomous Driving in Mines

With advancements in computer technology, the benefits of embodied intelligence are increasingly evident. This interactive learning model allows AI to be more flexibly deployed across diverse fields. Recent developments in multi-modal large language models (LLMs) have accelerated AI progress, especially in autonomous driving. This perspective highlights how embodied intelligence can enhance LLM applications in the mining industry, presenting new opportunities and potential to revolutionize the field. It also examines the challenges of deploying embodied agents in mining and offers insights into future research and development.

I. Introduction

Recently, the emergence of Large Language Model (LLM) has propelled artificial intelligence (AI) into unprecedented realms [1], ushering in a new era of text generation capabilities. The advent of LLMs not only advances AI in the realm of textual comprehension and generation but also catalyzes developments in related fields. Their integration with robotics undeniably injects fresh vigor into embodied intelligence.