卡车
自动化
软件部署
计算机科学
任务(项目管理)
重型的
系统工程
实时计算
工程类
运输工程
汽车工程
软件工程
机械工程
作者
Long Chen,Yuchen Li,Luxi Li,Shuangying Qi,Jian Zhou,Youchen Tang,Jianjian Yang,Jingmin Xin
标识
DOI:10.1109/tiv.2024.3375273
摘要
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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