Three dimensional unique identifier based automated georeferencing and coregistration of point clouds in underground environment
This addresses the challenge of monitoring underground or indoor environments like mines or tunnels for applications in civil, mining, and transportation, though it appears incremental as it builds on existing laser scanning practices.
The study tackled the problem of manual georeferencing and coregistration of laser scans in underground environments by developing an automated method using three-dimensional unique identifiers (3DUIDs), which was found to be accurate, effective, and efficient in field testing in an underground tunnel.
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.