自主无人机在危险矿区爆破后短时间内的安全检查和气体监测

IF 4.2 2区 计算机科学 Q2 ROBOTICS
Samuel Nordström, Nikolaos Stathoulopoulos, Niklas Dahlquist, Björn Lindqvist, Ilias Tevetzidis, Christoforos Kanellakis, George Nikolakopoulos
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引用次数: 0

摘要

本文介绍了有史以来第一次全自动无人机(无人驾驶飞行器)任务,在地下矿井发生真实爆炸后执行气体测量。示范任务在爆炸发生40分钟后部署,因此测量了真实的气体水平。我们还介绍了不同矿山的多个现场机器人实验,详细介绍了开发过程。提出了一种新的自治堆栈,称为例行检查自治(RIA)框架,结合了风险意识3D路径规划D + *,在已知地图上基于3D激光雷达的全球重新定位,并集成在定制硬件和带有机载气体传感设备的传感堆栈上。在提出的框架中,自动无人机可以在爆炸后不久部署在极其恶劣的条件下(灰尘,地图的显著变形),以执行对遗留气体的检查,这些气体对工人构成重大安全风险。我们还提出了一个变化检测框架,可以提取和可视化爆破过程中发生变化的区域,这是规划材料提取和更新现有矿山地图的关键参数。正如将展示的那样,RIA堆栈可以在恶劣条件下实现强大的自主性,并为自主例行检查任务提供可靠和安全的导航行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Safety Inspections and Gas Monitoring in Hazardous Mining Areas Shortly After Blasting Using Autonomous UAVs

Safety Inspections and Gas Monitoring in Hazardous Mining Areas Shortly After Blasting Using Autonomous UAVs

This article presents the first ever fully autonomous UAV (Unmanned Aerial Vehicle) mission to perform gas measurements after a real blast in an underground mine. The demonstration mission was deployed around 40 min after the blast took place, and as such realistic gas levels were measured. We also present multiple field robotics experiments in different mines detailing the development process. The presented novel autonomy stack, denoted as the Routine Inspection Autonomy (RIA) framework, combines a risk-aware 3D path planning D + * , with 3D LiDAR-based global relocalization on a known map, and it is integrated on a custom hardware and a sensing stack with an onboard gas sensing device. In the presented framework, the autonomous UAV can be deployed in incredibly harsh conditions (dust, significant deformations of the map) shortly after blasting to perform inspections of lingering gases that present a significant safety risk to workers. We also present a change detection framework that can extract and visualize the areas that were changed in the blasting procedure, a critical parameter for planning the extraction of materials, and for updating existing mine maps. As will be demonstrated, the RIA stack can enable robust autonomy in harsh conditions, and provides reliable and safe navigation behavior for autonomous Routine Inspection missions.

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来源期刊
Journal of Field Robotics
Journal of Field Robotics 工程技术-机器人学
CiteScore
15.00
自引率
3.60%
发文量
80
审稿时长
6 months
期刊介绍: The Journal of Field Robotics seeks to promote scholarly publications dealing with the fundamentals of robotics in unstructured and dynamic environments. The Journal focuses on experimental robotics and encourages publication of work that has both theoretical and practical significance.
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