A Framework Development for Mapping and Detecting Changes in Repeatedly Collected Massive Point Clouds

Yoon, Sanghyun; Ju, Sungha; Park, Sangyoon; Heo, Joon

doi:10.22260/isarc2019/0080

Cited by 2 publications

(2 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The target point cloud is indexed within the pre-existing MNO of the reference point cloud, established in the previous section. This indexing facilitates the computation of displacements for points within each individual MNO node in both the target and reference clouds, resulting in a significant reduction in computation time [ 10 , 76 ]. Figure 6 shows the indexing process of the target point cloud with the constructed MNO structure.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Automated Point Cloud Registration Approach Optimized for a Stop-and-Go Scanning System

Park,

Ju,

Nguyen

et al. 2023

Sensors

Self Cite

View full text Add to dashboard Cite

The latest advances in mobile platforms, such as robots, have enabled the automatic acquisition of full coverage point cloud data from large areas with terrestrial laser scanning. Despite this progress, the crucial post-processing step of registration, which aligns raw point cloud data from separate local coordinate systems into a unified coordinate system, still relies on manual intervention. To address this practical issue, this study presents an automated point cloud registration approach optimized for a stop-and-go scanning system based on a quadruped walking robot. The proposed approach comprises three main phases: perpendicular constrained wall-plane extraction; coarse registration with plane matching using point-to-point displacement calculation; and fine registration with horizontality constrained iterative closest point (ICP). Experimental results indicate that the proposed method successfully achieved automated registration with an accuracy of 0.044 m and a successful scan rate (SSR) of 100% within a time frame of 424.2 s with 18 sets of scan data acquired from the stop-and-go scanning system in a real-world indoor environment. Furthermore, it surpasses conventional approaches, ensuring reliable registration for point cloud pairs with low overlap in specific indoor environmental conditions.

show abstract

Section: Methodsmentioning

confidence: 99%

“…tation of displacements for points within each individual MNO node in both the target and reference clouds, resulting in a significant reduction in computation time [10,76]. Figure 6 shows the indexing process of the target point cloud with the constructed MNO structure.…”

Section: Overlapping Score With Point-to-point Displacementmentioning

confidence: 99%

Automated Point Cloud Registration Approach Optimized for a Stop-and-Go Scanning System

Park,

Ju,

Nguyen

et al. 2023

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

Interoperability of Digital Tools for the Monitoring and Control of Construction Projects

et al. 2021

View full text Add to dashboard Cite

Monitoring the progress on a construction site during the construction phase is crucial. An inadequate understanding of the project status can lead to mistakes and inappropriate actions, causing delays and increased costs. Monitoring and controlling projects via digital tools would reduce the risk of error and enable timely corrective actions. Although there is currently a wide range of technologies for these purposes, these technologies and interoperability between them are still limited. Because of this, it is important to know the possibilities of integration and interoperability regarding their implementation. This article presents a bibliographic synthesis and interpretation of 30 nonconventional digital tools for monitoring progress in terms of field data capture technologies (FDCT) and communication and collaborative technologies (CT) that are responsible for information processing and management. This research aims to perform an integration and interoperability analysis of technologies to demonstrate their potential for monitoring and controlling construction projects during the execution phase. A network analysis was conducted, and the results suggest that the triad formed by building information modeling (BIM), unmanned aerial vehicles (UAVs) and photogrammetry is an effective tool; the use of this set extends not only to monitoring and control, but also to all phases of a project.

show abstract

A Framework Development for Mapping and Detecting Changes in Repeatedly Collected Massive Point Clouds

Cited by 2 publications

References 20 publications

Automated Point Cloud Registration Approach Optimized for a Stop-and-Go Scanning System

Automated Point Cloud Registration Approach Optimized for a Stop-and-Go Scanning System

Interoperability of Digital Tools for the Monitoring and Control of Construction Projects

Contact Info

Product

Resources

About