Automated mapping for underground pipelines: An overview

TLDR: It is indicated 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 and the need for the implementation of Simultaneous Localization and Mapping (SLAM) algorithm.

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.