Machine and deep learning for digital twin networks: A survey

B Qin, H Pan, Y Dai, X Si, X Huang… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
Digital twin (DT) is a technology that precisely replicates physical entities and seamlessly
connects physical entities with virtual counterparts, which facilitates precise understanding …

Scenario engineering for autonomous transportation: A new stage in open-pit mines

S Teng, X Li, Y Li, L Li, Z Xuanyuan… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In recent years, open-pit mining has seen significant advancement, the cooperative
operation of various specialized machinery substantially enhancing the efficiency of mineral …

High-precision positioning, perception and safe navigation for automated heavy-duty mining trucks

L Chen, Y Li, L Li, S Qi, J Zhou, Y Tang… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Autonomous driving technology has achieved significant breakthroughs in open scenarios,
enabling the deployment of excellent positioning, detection, and navigation algorithms on …

OmniHD-Scenes: A next-generation multimodal dataset for autonomous driving

L Zheng, L Yang, Q Lin, W Ai, M Liu, S Lu, J Liu… - arxiv preprint arxiv …, 2024 - arxiv.org
The rapid advancement of deep learning has intensified the need for comprehensive data
for use by autonomous driving algorithms. High-quality datasets are crucial for the …

Miningllm: Towards mining 5.0 via large language models in autonomous driving and smart mining

Y Li, L Li, Z Wu, Z Bing, Y Ai, B Tian… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Minerals serve as the cornerstone of contemporary societal infrastructure and diverse
industries. However, the mining sector perennially confronts transportation challenges …

Embodied Intelligence in Mining: Leveraging Multi-modal Large Language Model for Autonomous Driving in Mines

L Li, Y Li, X Zhang, Y He, J Yang, B Tian… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
With advancements in computer technology, the benefits of embodied intelligence are
increasingly evident. This interactive learning model allows AI to be more flexibly deployed …

SXAD: Shapely eXplainable AI-Based Anomaly Detection Using Log Data

K Alam, K Kifayat, GA Sampedro, V Karovič… - IEEE …, 2024 - ieeexplore.ieee.org
Artificial Intelligence (AI) has made tremendous progress in anomaly detection. However, AI
models work as a black-box, making it challenging to provide reasoning behind their …

AutoMine: A Multimodal Dataset for Robot Navigation in Open‐Pit Mines

Y Li, S Teng, J Wang, Y Ai, B Tian… - Journal of Field …, 2024 - Wiley Online Library
In the past decade, autonomous driving has witnessed significant advancements, largely
attributable to the evolution of precise algorithms and efficient computing platforms …

Active Parallel Teacher for Human-in-the-Loop Sim2Real Object Detection in Autonomous Haulage Trucks

L Guo, Y Guo, Y Ai, S Ge - IEEE Transactions on Intelligent …, 2024 - ieeexplore.ieee.org
Object detection for autonomous haulage trucks in open-pit mines is challenging due to
unstructured environments. Collecting and annotating large-scale real-world images in …

Real-Time Efficient Environment Compression and Sharing for Multi-Robot Cooperative Systems

L Zheng, K Xu, J Jiang, M Wei, B Zhou… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Efficient environment sharing is crucial for multi-robot tasks, such as exploration and
navigation. However, real-time environment sharing faces significant challenges due to …