Embodied Intelligence in Mining: Leveraging Multi-Modal Large Language Models for Autonomous Driving in Mines-Reference-Cited by-同舟云学术

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

Published:2024-05 Issue:5 Volume:9 Page:4831-4834
ISSN:2379-8904
Container-title:IEEE Transactions on Intelligent Vehicles
language:
Short-container-title:IEEE Trans. Intell. Veh.

Author:

Li Luxi¹^ORCID,Li Yuchen¹^ORCID,Zhang Xiaotong²^ORCID,He Yuhang³^ORCID,Yang Jianjian⁴^ORCID,Tian Bin²^ORCID,Ai Yunfeng²^ORCID,Li Lingxi⁵^ORCID,Nüchter Andreas⁶^ORCID,Xuanyuan Zhe⁷^ORCID

Affiliation:

1. Faculty of Science and Technology, BNU-HKBU United International College, Zhuhai, China

2. Institution of Automation, Chinese Academy of Sciences, Beijing, China

3. University of Oxford, Oxford, U.K.

4. China University of Mining and Technology (Beijing), Beijing, China

5. Purdue University, West Lafayette, IN, USA

6. Informatics XVII - Robotics, Julius Maximilian University, Würzburg, Germany

7. Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science, BNU-HKBU United International College, Zhuhai, China

Funder

Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science, BNU-HKBU United International College

Guangdong Higher Education Upgrading Plan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/7274857/10613449/10569079.pdf?arnumber=10569079

Reference22 articles.

1. A commentary of GPT-3 in MIT Technology Review 2021

2. From machine learning to robotics: Challenges and opportunities for embodied intelligence;Roy,2021

3. Traffic Flow Imputation Using Parallel Data and Generative Adversarial Networks

4. Parallel Intelligence in CPSSs: Being, Becoming, and Believing

5. Scenario Engineering for Autonomous Transportation: A New Stage in Open-Pit Mines