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State of the Art in Terrestrial Laser Scanning
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State of the Art in Terrestrial Laser Scanning

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".

Deadline for manuscript submissions: closed (25 September 2022) | Viewed by 11935

Special Issue Editor

Dr. Bala Muralikrishnan

E-Mail Website
Guest Editor
Sensor Science Division, National Institute of Standards and Technology (NIST), Gaithersburg, MD 20899, USA
Interests: TLS error modelling and applications; large scale dimensional metrology; documentary standards; measurement uncertainty

Special Issue Information

Dear Colleagues,

Static terrestrial laser scanners (TLSs) are increasingly being used for a variety of applications such as forensic crime scene preservation, historical monument digitization, surveying and geodesy, reverse engineering, and manufacturing and assembly. The level of tolerance required for these tasks ranges from a few millimeters to a few micrometers, depending on the application. The characterization of TLS error sources and development of calibration procedures are key aspects in ensuring the realiability of data obtained from these systems. With the publication of the ASTM E2938-15, ASTM E3125-17, and ISO 17123-9 standards, users now have access to standardized procedures for evaluating the performance of these systems. In this context, this Special Issue focuses on the state-of-the-art in TLS technology with emphasis on novel applications, error sources, calibration, measurement uncertainty, and performance evaluation. Topics of interest include but are not limited to

  • TLS applications;
  • Modeling and characterizing errors;
  • Computational aspects in TLS usage;
  • Registration, feature extraction, and data fusion;
  • Self-calibration
  • Performance evaluation and documentary standards
  • Field check procedures;
  • Uncertainty in TLS measurements

Dr. Bala Muralikrishnan
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (2 papers)

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Research

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20 pages, 12455 KiB  
Article
Study on TLS Point Cloud Registration Algorithm for Large-Scale Outdoor Weak Geometric Features
by Chen Li, Yonghua Xia, Minglong Yang and Xuequn Wu
Sensors 2022, 22(14), 5072; https://0-doi-org.brum.beds.ac.uk/10.3390/s22145072 - 06 Jul 2022
Cited by 5 | Viewed by 1816
Abstract
With the development of societies, the exploitation of mountains and forests is increasing to meet the needs of tourism, mineral resources, and environmental protection. The point cloud registration, 3D modeling, and deformation monitoring that are involved in surveying large scenes in the field [...] Read more.
With the development of societies, the exploitation of mountains and forests is increasing to meet the needs of tourism, mineral resources, and environmental protection. The point cloud registration, 3D modeling, and deformation monitoring that are involved in surveying large scenes in the field have become a research focus for many scholars. At present, there are two major problems with outdoor terrestrial laser scanning (TLS) point cloud registration. First, compared with strong geometric conditions with obvious angle changes or symmetric structures, such as houses and roads, which are commonly found in cities and villages, outdoor TLS point cloud registration mostly collects data on weak geometric conditions with rough surfaces and irregular shapes, such as mountains, rocks, and forests. This makes the algorithm that set the geometric features as the main registration parameter invalid with uncontrollable alignment errors. Second, outdoor TLS point cloud registration is often characterized by its large scanning range of a single station and enormous point cloud data, which reduce the efficiency of point cloud registration. To address the above problems, we used the NARF + SIFT algorithm in this paper to extract key points with stronger expression, expanded the use of multi-view convolutional neural networks (MVCNN) in point cloud registration, and adopted GPU to accelerate the matrix calculation. The experimental results have demonstrated that this method has greatly improved registration efficiency while ensuring registration accuracy in the registration of point cloud data with weak geometric features. Full article
(This article belongs to the Special Issue State of the Art in Terrestrial Laser Scanning)
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Review

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32 pages, 44602 KiB  
Review
Application of Terrestrial Laser Scanning (TLS) in the Architecture, Engineering and Construction (AEC) Industry
by Chao Wu, Yongbo Yuan, Yang Tang and Boquan Tian
Sensors 2022, 22(1), 265; https://0-doi-org.brum.beds.ac.uk/10.3390/s22010265 - 30 Dec 2021
Cited by 55 | Viewed by 8842
Abstract
As a revolutionary technology, terrestrial laser scanning (TLS) is attracting increasing interest in the fields of architecture, engineering and construction (AEC), with outstanding advantages, such as highly automated, non-contact operation and efficient large-scale sampling capability. TLS has extended a new approach to capturing [...] Read more.
As a revolutionary technology, terrestrial laser scanning (TLS) is attracting increasing interest in the fields of architecture, engineering and construction (AEC), with outstanding advantages, such as highly automated, non-contact operation and efficient large-scale sampling capability. TLS has extended a new approach to capturing extremely comprehensive data of the construction environment, providing detailed information for further analysis. This paper presents a systematic review based on scientometric and qualitative analysis to summarize the progress and the current status of the topic and to point out promising research efforts. To begin with, a brief understanding of TLS is provided. Following the selection of relevant papers through a literature search, a scientometric analysis of papers is carried out. Then, major applications are categorized and presented, including (1) 3D model reconstruction, (2) object recognition, (3) deformation measurement, (4) quality assessment, and (5) progress tracking. For widespread adoption and effective use of TLS, essential problems impacting working effects in application are summarized as follows: workflow, data quality, scan planning, and data processing. Finally, future research directions are suggested, including: (1) cost control of hardware and software, (2) improvement of data processing capability, (3) automatic scan planning, (4) integration of digital technologies, (5) adoption of artificial intelligence. Full article
(This article belongs to the Special Issue State of the Art in Terrestrial Laser Scanning)
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