Automated mapping for underground pipelines: An overview

N. M. Yatim, R. Shauri, N. Buniyamin
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引用次数: 15

Abstract

Autonomous robot platform for pipeline inspection is a preferred alternative to efficiently monitor pipeline condition. A large number of research in the area of inspection robot focuses on corrosion detection and navigation. There is however a smaller number of researchers that investigates mapping and detection of underground and buried pipeline network/routes. This paper presents an overview of research in the area of automated mapping of underground pipelines. There is a need to map underground pipelines due to non-availability of maps and network diagrams of existing pipelines caused by poor documentation management and poor updating of documentation whenever piping rerouting occurs. An accurate map also could be used by an autonomous inspection robot for navigation and localization. An autonomous inspection robot that can accurately detect pipelines could then be used to detect misalignment and deformities of pipeline structures and network. This investigation indicates that to design an automated mapping system for underground pipelines, researchers must consider the type of sensors that can be used underground and in a metal environment. The investigation also points out the need for the implementation of Simultaneous Localization and Mapping (SLAM) algorithm and the right map representation such as occupancy grid map to map the pipelines route as it could produce a more accurate map with preferred type of sensors.
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地下管线的自动测绘:概述
自主机器人管道检测平台是有效监测管道状态的首选替代方案。在检测机器人领域的大量研究集中在腐蚀检测和导航方面。然而,研究地下和埋地管道网络/路线的测绘和探测的研究人员较少。本文介绍了地下管线自动测绘领域的研究概况。由于文件管理不善和每当管道改道时文件更新不力,现有管道的地图和网络图无法获得,因此需要绘制地下管道图。精确的地图也可以被自动检测机器人用于导航和定位。能够准确检测管道的自主检测机器人可以用于检测管道结构和网络的错位和变形。这项研究表明,为了设计地下管道的自动测绘系统,研究人员必须考虑可以在地下和金属环境中使用的传感器类型。调查还指出,需要实施同步定位和地图(SLAM)算法和正确的地图表示,如占用网格地图,以绘制管道路线,因为它可以产生更准确的地图与首选类型的传感器。
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