Three dimensional unique identifier based automated georeferencing and coregistration of point clouds in underground environment

TL;DR

This paper introduces a novel automated method using 3D unique identifiers for precise georeferencing and coregistration of point clouds in underground environments, addressing challenges like occlusions and repetitive features.

Contribution

It presents a new approach with 3DUIDs and a 3D registration workflow that improves accuracy and efficiency in underground laser scanning applications.

Findings

Field testing in an underground tunnel showed high accuracy.

The method effectively handles structural symmetry and occlusions.

Automatic roadway profile extraction was successfully demonstrated.

Abstract

Spatially and geometrically accurate laser scans are essential in modelling infrastructure for applications in civil, mining and transportation. Monitoring of underground or indoor environments such as mines or tunnels is challenging due to unavailability of a sensor positioning framework, complicated structurally symmetric layouts, repetitive features and occlusions. Current practices largely include a manual selection of discernable reference points for georeferencing and coregistration purpose. This study aims at overcoming these practical challenges in underground or indoor laser scanning. The developed approach involves automatically and uniquely identifiable three dimensional unique identifiers (3DUIDs) in laser scans, and a 3D registration (3DReG) workflow. Field testing of the method in an underground tunnel has been found accurate, effective and efficient. Additionally, a method for automatically extracting roadway tunnel profile has been exhibited. The developed 3DUID can be used in roadway profile extraction, guided automation, sensor calibration, reference targets for routine survey and deformation monitoring.