Data quality oriented 3d laser scan planning

Mingming Song, Zhenglai Shen, Pingbo Tang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

Point clouds collected by laser scanners have been used in various architecture, engineering, and construction (AEC) projects. Effective uses of laser scanners on job sites require reducing the interferences of data collection with field activities while ensuring the data quality. Existing laser scan planning methods focused on visibility analysis with limited considerations about the level of detail (LOD) of collected point clouds even though LOD is a function of factors other than visibility. This limitation leads to insufficient LOD of certain features in point clouds for decision support. This paper presents a laser scan planning approach that integrates geometric feature clustering and data quality checking methods for addressing this limitation. The inputs of this approach include an as-designed model integrating LOD requirements of geometric features. The algorithm first clusters geometric features to reduce the computational complexity of scan planning. It then uses a sensor model of laser scanning to generate a "feasible space" for scanning each cluster of features. After that, it assesses the number of features covered at candidate scanning locations and pinpoints scanning positions covering more features with less scans. The results in a case study show that this approach outperforms manual scan planning in data's LOD.

Original languageEnglish (US)
Title of host publicationConstruction Research Congress 2014: Construction in a Global Network - Proceedings of the 2014 Construction Research Congress
PublisherAmerican Society of Civil Engineers (ASCE)
Pages984-993
Number of pages10
ISBN (Print)9780784413517
DOIs
StatePublished - 2014
Event2014 Construction Research Congress: Construction in a Global Network, CRC 2014 - Atlanta, GA, United States
Duration: May 19 2014May 21 2014

Other

Other2014 Construction Research Congress: Construction in a Global Network, CRC 2014
CountryUnited States
CityAtlanta, GA
Period5/19/145/21/14

Fingerprint

Planning
Lasers
Scanning
Visibility
Computational complexity
Sensors

ASJC Scopus subject areas

  • Building and Construction

Cite this

Song, M., Shen, Z., & Tang, P. (2014). Data quality oriented 3d laser scan planning. In Construction Research Congress 2014: Construction in a Global Network - Proceedings of the 2014 Construction Research Congress (pp. 984-993). American Society of Civil Engineers (ASCE). https://doi.org/10.1061/9780784413517.0101

Data quality oriented 3d laser scan planning. / Song, Mingming; Shen, Zhenglai; Tang, Pingbo.

Construction Research Congress 2014: Construction in a Global Network - Proceedings of the 2014 Construction Research Congress. American Society of Civil Engineers (ASCE), 2014. p. 984-993.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Song, M, Shen, Z & Tang, P 2014, Data quality oriented 3d laser scan planning. in Construction Research Congress 2014: Construction in a Global Network - Proceedings of the 2014 Construction Research Congress. American Society of Civil Engineers (ASCE), pp. 984-993, 2014 Construction Research Congress: Construction in a Global Network, CRC 2014, Atlanta, GA, United States, 5/19/14. https://doi.org/10.1061/9780784413517.0101
Song M, Shen Z, Tang P. Data quality oriented 3d laser scan planning. In Construction Research Congress 2014: Construction in a Global Network - Proceedings of the 2014 Construction Research Congress. American Society of Civil Engineers (ASCE). 2014. p. 984-993 https://doi.org/10.1061/9780784413517.0101
Song, Mingming ; Shen, Zhenglai ; Tang, Pingbo. / Data quality oriented 3d laser scan planning. Construction Research Congress 2014: Construction in a Global Network - Proceedings of the 2014 Construction Research Congress. American Society of Civil Engineers (ASCE), 2014. pp. 984-993
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