TY - GEN
T1 - Sensor modeling of laser scanners for automated scan planning on construction jobsites
AU - Tang, Pingbo
AU - Alaswad, Fahd Saleh
PY - 2012
Y1 - 2012
N2 - A challenge of using terrestrial laser scanners on jobsites is to effectively plan the scanning locations and configure scanners' technical parameters according to the domain requirements and site conditions. With time limits in the field, it is challenging to manually design and analyze scanning plans considering technical capabilities of scanners and environmental conditions (e.g., occlusions) for ensuring that all needed spatial information is captured with the required levels of accuracy and detail. In addition, the information requirements of construction tasks may vary spatially and temporally, further complicating the scan planning. These facts can lead to longer data collection time, unexpected interferences on jobsites, and missing data. This paper proposes an approach of automated laser scan planning based on sensor models of terrestrial laser scanners. We developed a sensor model capturing the relationships between various data collection parameters (e.g., data collection distances) and data quality metrics (e.g., accuracies and densities of 3D point clouds). Given the user-specified data quality requirements, an optimization algorithm can use this sensor model to identify scanning plans that minimize the data collection time while optimizing the data qualities and spatial information coverage.
AB - A challenge of using terrestrial laser scanners on jobsites is to effectively plan the scanning locations and configure scanners' technical parameters according to the domain requirements and site conditions. With time limits in the field, it is challenging to manually design and analyze scanning plans considering technical capabilities of scanners and environmental conditions (e.g., occlusions) for ensuring that all needed spatial information is captured with the required levels of accuracy and detail. In addition, the information requirements of construction tasks may vary spatially and temporally, further complicating the scan planning. These facts can lead to longer data collection time, unexpected interferences on jobsites, and missing data. This paper proposes an approach of automated laser scan planning based on sensor models of terrestrial laser scanners. We developed a sensor model capturing the relationships between various data collection parameters (e.g., data collection distances) and data quality metrics (e.g., accuracies and densities of 3D point clouds). Given the user-specified data quality requirements, an optimization algorithm can use this sensor model to identify scanning plans that minimize the data collection time while optimizing the data qualities and spatial information coverage.
KW - Automation
KW - Construction management
KW - Inspection planning
KW - Laser scanning
KW - Sensor modeling
UR - http://www.scopus.com/inward/record.url?scp=84866245589&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84866245589&partnerID=8YFLogxK
U2 - 10.1061/9780784412329.103
DO - 10.1061/9780784412329.103
M3 - Conference contribution
AN - SCOPUS:84866245589
SN - 9780784412329
T3 - Construction Research Congress 2012: Construction Challenges in a Flat World, Proceedings of the 2012 Construction Research Congress
SP - 1021
EP - 1031
BT - Construction Research Congress 2012
T2 - Construction Research Congress 2012: Construction Challenges in a Flat World
Y2 - 21 May 2012 through 23 May 2012
ER -