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

IF 14 1区工程技术 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE IEEE Transactions on Intelligent Vehicles Pub Date : 2024-03-01 DOI:10.1109/TIV.2024.3417938

Luxi Li;Yuchen Li;Xiaotong Zhang;Yuhang He;Jianjian Yang;Bin Tian;Yunfeng Ai;Lingxi Li;Andreas Nüchter;Zhe Xuanyuan

引用次数: 0

Abstract

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.

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采矿中的嵌入式智能：利用多模态大语言模型实现矿山自动驾驶

随着计算机技术的进步，具身智能的优势日益明显。这种交互式学习模式使人工智能可以更灵活地应用于各个领域。多模式大型语言模型（LLM）的最新发展加速了人工智能的进步，尤其是在自动驾驶领域。本视角重点介绍了具身智能如何增强 LLM 在采矿业中的应用，从而为该领域的变革带来新的机遇和潜力。它还探讨了在采矿业部署具身代理所面临的挑战，并对未来的研究与发展提出了见解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Intelligent Vehicles Mathematics-Control and Optimization

CiteScore

12.10

自引率

13.40%

发文量

177

期刊介绍： The IEEE Transactions on Intelligent Vehicles (T-IV) is a premier platform for publishing peer-reviewed articles that present innovative research concepts, application results, significant theoretical findings, and application case studies in the field of intelligent vehicles. With a particular emphasis on automated vehicles within roadway environments, T-IV aims to raise awareness of pressing research and application challenges. Our focus is on providing critical information to the intelligent vehicle community, serving as a dissemination vehicle for IEEE ITS Society members and others interested in learning about the state-of-the-art developments and progress in research and applications related to intelligent vehicles. Join us in advancing knowledge and innovation in this dynamic field.

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