High-Precision Positioning, Perception and Safe Navigation for Automated Heavy-Duty Mining Trucks

IF 14 1区工程技术 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

IEEE Transactions on Intelligent Vehicles Pub Date : 2024-03-14 DOI:10.1109/TIV.2024.3375273

Long Chen;Yuchen Li;Luxi Li;Shuangying Qi;Jian Zhou;Youchen Tang;Jianjian Yang;Jingmin Xin

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Abstract

Autonomous driving technology has achieved significant breakthroughs in open scenarios, enabling the deployment of excellent positioning, detection, and navigation algorithms on passenger vehicles. However, there has been limited research attention devoted to autonomous driving for specialized vehicles in non-open scenarios. This manuscript introduces a perception system designed for heavy-duty mining transportation trucks operating in open-pit mines, which are typical of non-open scenarios. The system comprises four independent algorithms: high-precision fusion positioning, multi-task 2D detection, 9 Degrees of Freedom (9 DoF) 3D head, and autonomous navigation technology. Experimental verification demonstrates the effectiveness of these methods in addressing the challenges posed by mining environments, ultimately leading to enhanced safety and efficiency for trucks. This research outcome, through the comprehensive examination of positioning, detection, and navigation, aims to address the challenges encountered by mining trucks during operations. Its significance lies in enhancing automation levels in mining scenarios.

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重型自动采矿车的高精度定位、感知和安全导航

自动驾驶技术在开放场景中取得了重大突破，在乘用车上部署了出色的定位、检测和导航算法。然而，人们对非开放场景下专用车辆自动驾驶的研究关注却很有限。本手稿介绍了一种感知系统，该系统专为在露天矿中运行的重型采矿运输卡车而设计，露天矿是典型的非开放场景。该系统由四种独立算法组成：高精度融合定位、多任务二维检测、9 自由度（9 DoF）三维头部和自主导航技术。实验验证证明了这些方法在应对采矿环境挑战方面的有效性，最终提高了卡车的安全性和效率。这项研究成果通过对定位、检测和导航的全面检查，旨在解决采矿卡车在作业过程中遇到的挑战。其意义在于提高采矿场景中的自动化水平。

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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.